A “blood count”, “complete blood count”, or “blood cell profile” commonly designates a set of tests to determine the number, ratio and appearances of blood cells and/or their cellular subgroups (e.g., neutrophils, eosinophils, basophils, CD19 or CD3 cells, and their subgroups, such as CD3+CD4+ and/or CD3+/CD8+ cells). Such a blood count is used in clinical diagnostics as a broad screening test for disorders or a determination of the general health status of an individual. In general, a “blood count” includes assays directed at hematocrit, quantification of hemoglobin, total blood cells, and red blood cell index (e.g. mean corpuscular volume, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, red blood cell distribution).
White blood cells (also referred to as leukocytes) are part of the cellular immune system (we explicitly define all immune cells, including B-cells as cellular immune system) and play a key role in defending an mammals from pathological effects caused either by foreign organisms (in particular for example: viruses, bacteria, parasites, etc.), but also from aberrations of diseased self-cells, such as tumor cells. In addition, immune cells are themselves subject to diseases, either as primary (congenital) immune diseases, such as the IPEX syndrome or as secondary (acquired) immune diseases, such as for example AIDS, HIV. In the former, the immune system itself is impaired, whereas in the latter external factors (such as virus infections, radiation, chemotherapies or environmental factors) lead to a weakening of the immune system. Several types of leukocytes exist and they either derive from the myeloid lineage—e.g. neutrophil, eosinophil and basophil granulocytes, mast cells and macrophages—or derive from the lymphoid lineage including all lymphocyte subpopulations—such as for example T-cells, B-cells, NK cells. Since the composition of the immune system, and its cellular members, has been subjected to many analyses, aberrations of this normal immune cell count (or ratio) can be recognized easily, is used diagnostically, and may be used for clinical decision-making. Thus, the ratio and count of these cells are regularly analyzed in clinical settings—both as routine diagnostic or analytical tool as well as in clinical research or trials—in order to detect any abnormalities or apparent changes that may be caused by a disease or a disease treatment or other internal or external factors. For example, blood counts are used to diagnose the onset/occurence of leuko- or lymphopenias or leuko- or lymphocytosis, such as granulocytosis. Furthermore, blood counts are taken to monitor the treatment success of all diseases that result from, cause or whose treatment may result in changes of the overall or specific leuko- or lymphocyte counts. For example, for diagnosing or monitoring infections, anemia, leukemia or the effects of chemotherapies, a so-called “differential” whole blood count is used in order to analyze and identify immune cells and subpopulations thereof. In some primary and secondary immune disorders, this procedure may be the only available diagnostic tool. The differential blood count includes assays directed at a quantification of total white blood cells, neutrophil granulocytes, lymphocytes, monocytes, eosinophil granulocytes, and basophil granulocytes.
Routinely, for soluble cells, i.e., mainly blood but also solubilized tissues or body fluids such a specific immune cell profile is measured by flow cytometry, or by immunohistochemistry (IHC) for solid tissues. Both technologies work on the basis of protein epitopes exposed on cell membranes that are specific for each subtype of cell subpopulation. Recently, research focused on the biological role of leukocyte subpopulations, and this results in a strong demand for clinical as well as for research applications allowing to identifying such populations.
Technically, in routine diagnostics, hematocrit, hemoglobin as well as total white blood counts are determined by an automatic cell counter based on light detection and electrical impedance. A differential white blood count, including neutrophil, eosinophil, basophil granulocytes, monocytes and mast cells are determined either via manual microscopic counting or automatic counting of blood smears.
Additional methods, allowing for the detection of T cell populations are MHC multimetric analyses, the Cytokine-Capture Assay, individual T cell detections (ELISPOT-Assay) or the merely qualitative detection and localization of immune cells (immunohistochemical analyses). Like flow cytometry, these assays are based on a detection of proteins; no specific expression level-independent markers are used. It is noteworthy that all of these assays as well as all assays based on the detection of mRNA, vary from cell to cell. This is because even cells that are undoubtedly positive for a certain protein present time wise varying amounts of protein. Hence, a threshold for “positivity” has to be determined for each and every protein marker depending on the affinity and unspecific binding properties of the given antibody as well as on the average amount of surface expression of the target protein.
Even though almost all cells in an individual contain the exact same complement/composition of DNA code, higher organisms must impose and maintain different patterns of gene expression in the various types of tissue. Most gene regulation is transitory, depending on the current state of the cell and changes in external stimuli. Persistent regulation, on the other hand, is a primary role of epigenetics—heritable regulatory patterns that do not alter the basic genetic coding of the DNA. DNA methylation is the archetypical form of epigenetic regulation; it serves as the stable memory for cells and performs a crucial role in maintaining the long-term identity of various cell types. Recently, other forms of epigenetic regulation were discovered. In addition to the “fifth base” 5-methylcytosine (mC), a sixth (5-hydroxymethylcytosine, hmC), seventh (5-formylcytosine, fC) and eighth (5-carboxycytosine, cC) can be found (Michael J. Booth et al. Quantitative Sequencing of 5-Methylcytosine and 5-Hydroxymethylcytosine at Single-Base Resolution Science 18 May 2012, Vol. 336 no. 6083 pp. 934-937). The primary target of mentioned DNA modifications is the two-nucleotide sequence Cytosine-Guanine (a ‘CpG site’); within this context cytosine (C) can undergo a simple chemical modification to become formylated, methylated, hydroxymethylated, or carboxylated. In the human genome, the CG sequence is much rarer than expected, except in certain relatively dense clusters called ‘CpG islands’. CpG islands are frequently associated with gene promoters, and it has been estimated that more than half of the human genes have CpG islands (Antequera and Bird, Proc Natl Acad Sci USA 90: 11995-9, 1993).
For one of the recently described modification of cytosine, 5-hydroxymethylation, the utility of oxidative bisulfite sequencing to map and quantify 5hmC at CpG islands was shown (Michael J. Booth et al. Quantitative Sequencing of 5-Methylcytosine and 5-Hydroxymethylcytosine at Single-Base Resolution Science 18 May 2012, Vol. 336 no. 6083 pp. 934-937).
In the context of the present invention, the term “bisultite convertible chromatin” shall mean a chromatin structure (e.g. a sufficiently opened structure) that allows bisulfite to chemically modify cytosines. Consequently, the term “DNA bisulfite convertibility” relates to the extent of cytosine bases in said chromatin and/or the respective nucleic acid that is part of said chromatin, that can be (or have been) converted using a bisulfite treatment. The term also relates to the extent of cytosine bases in a reference nucleic acid (such as a plasmid) that can be (or have been) converted using a bisulfite treatment. In turn, the term “non-bisulfite convertible chromatin” or “non-bisulfite convertible nucleic acid” relates to the extent of cytosine bases that cannot be (or could not been) converted using a bisulfite treatment.
As mentioned above, recently three new cytosine modifications were discovered. Therefore, it is expected that future scientific findings will lead to a more precise interpretation of epigenetic patterns of bisulfite convertibility described in the past. These past result of cytosine modification encompass bisulfite convertible (non-methylated, non-modified) and non-convertible (methylated, modified) cytosine. Both termini need to be reinterpreted, as described. According to the novel scientific findings (i) non-bisulfite convertible cytosine encompasses 5-methylcytosine (mC) and 5-hydroxymethylcytosine (hmC), and (ii) bisulfite convertible cytosine encompasses 5-formylcytosine (fC), 5-carboxycytosine (cC) as well as non-modified cytosine.
Additionally, earlier inventions are based on (i) the ratio of bisulfite convertible cytosine to whole amount of chromatin (cell-type independent, 100% bisulfite convertible DNA locus) or (ii) on the ratio of bisulfite convertible cytosine (fC, cC, non-modified cytosine) to non-bisulfite convertible cytosine (hmC and mC). These ratios are used to characterize cell type, cell differentiation, cell stage as well as pathological cell stages. Therefore, new techniques will result in novel, more specific ratios and might supplement current cell specific, cell state specific as well as pathological patterns of epigenetic modifications and therefore, define potential novel biomarkers. Novel ratios to be discovered as biomarkers can be defined as:Biomarker Ratio=a/b a=Σ(C and/or mC and/or hmC and/or fC and/or cC)b=Σ(C and/or mC and/or hmC and/or fC and/or cC),whereby a and b differs from each other by one to four kinds of modifications. Discovery of novel DNA modifications will certainly broaden this enumeration.
For the purpose of the present application, epigenetic modifications in the DNA sequence is referred to by the terminology of (i) bisulfite convertible cytosine (5-formylcytosine, (fC) and/or 5-carboxycytosine (cC)) and (ii) non-bisulfite convertible cytosine ((including 5-methylcytosine (mC), 5-hydroxymethylcytosine, (hmC)). As both kinds of methylation, mC and hmC are not bisulfite convertible it is not possible to distinguish between these two. Likewise, fC, cC as well as non-modified cytosine are bisulfite convertible and can also not be distinguished from each other as well.
Furthermore, apart from the modifications of DNA also histones undergo posttranslational modifications that alter their interaction with DNA and nuclear proteins. Modifications include methylation, acetylation, phosphorylation, ubiquitination, sumoylation, citrullination, and ADPribosylation. The core of the histones H2A, H2B, and H3 can also be modified. Histone modifications act in diverse biological processes such as gene regulation, DNA repair, chromosome condensation (mitosis) and spermatogenesis (meiosis). Also for these modifications a specific pattern of modification is specific for different cell types, cell stages, differentiation status and such a pattern can be analyzed for bisulfite convertibility or similar methods in order to identify certain cells and cell stages. The present invention also encompasses a use of these modifications.
It is expected that further variants of DNA modifications will be discovered in future. Each type of modification will be either bisulfite-convertible or not. These novel modifications can also be used as biomarker readout. Additionally, it is expected that novel methods for bisulfite modification will be established, resulting in a different set of convertible and non-convertible DNA.
The variety of indications for which reporting of the cellular immune status is clinically or analytically helpful is very large. For almost every disease the cellular immune status is either directly relevant or—such as in cancer—becomes relevant due to the impact of drugs that may cause secondary immunological disorders and aberrations. This broad significance of the overall immune status in diseases settings results in a significant demand for methods to measure these parameters, i.e., the leukocyte subtypes and subpopulations.
The current way of addressing this demand is by flow cytometric and immunohistochemical methods, which are well-established and have been developed into high throughput systems for hospital use, are standard procedures in reference laboratories and are, for more simple applications, made available for practitioners. However, certain problems and requirements limit the applicability of flow cytometry and immunohistochemistry.
a) For flow cytometry, cells need to be intact. This means that the blood sample has to be measured in a “fresh” state, any delay in measurement may lead to deviation of results. As a rule of thumb, samples should be measured within 8 hours, since after that time frame granulocytes (one main cellular fraction in the blood) begin to disintegrate. As an alternative to fresh handling, it is possible to cryopreserve blood samples, but there are significant issues associated with respect to performance and reproducibility. As a consequence, flow cytometry in clinical routine is avoided and many potentially meaningful analyzes are omitted, whereas in clinical trials, where immune markers are prime biomarker candidates for treatment predictions, are often left out, or if required by regulations extra facilities need to be set up.
b) Antigen expression is not a digital (on-off), but an analog (low, medium, high) process. Therefore, thresholds defining positive versus negative signals must be determined. For certain markers, this is unproblematic, for others thresholds are very difficult and imprecise.
c) For flow cytometry, it also poses problems that many cell types are not simply identified by a surface (cluster of differentiation—CD) molecule, but some cell types are characterized by intra- or extracellular soluble proteins, e.g. transcription factors or cytokines. Current markers for Tfh, Th1, Th2 cells, and Tregs belong to this category of cell types—the application of fully standardized procedures is even more difficult. This is because the cell-type specific markers need to be captured in order to be associated to the cell.
d) Furthermore, flow cytometry is dependent on the solubility of the analyzed substrate (cell suspensions). With respect to this, tissue cells may be solubilized by enzymatic digestion, but this often leads to the loss of their surface molecules—rendering the CD markers, as prime targets for flow cytometric analysis useless.
e) Often, neither surface- nor intra- or extracellular markers are 100% cell-type specific. “Leaky” expression of certain gene products has been reported (Wiezcorek et al., Cancer Res. 2009 Jan. 15; 69(2):599-608), rendering the quantification somewhat imprecise.
f) Since immunohistochemistry is based on the same principle as flow cytometry, specificity problems overlap. However, the main problem with this technology is that it is considered only semiquantitative. In particular, a particular problem is that an overall cell counting is not feasible due to the presence of various different cell layers, which are difficult to distinguish and count correctly.
As far as aspect e) is concerned, the inventors have previously published a publication proving that flow cytometry detects expressed surface epitopes, but it cannot distinguish between cell-type specific epitope expression and cell-type independent induction of epitope expressions as well as it cannot detect specific-cells that currently not express or less express certain surface markers. In vitro stimulation of CD4+CD25+CD45RA+ T cells, for example, leads to a high expression level of FOXP3 whereby the FOXP3 gene is still methylated and therefore inactivated (Baron et al., Epigenetics. 2006 January-March; 1(1):55-60). Additionally, for in vitro differentiated Th17 cells no demethylation of IL-17A promotor was observed despite high levels of IL-17A transcripts (Janson P. C. J. et al. Profiling of CD4+ T cells with epigenetic immune lineage analysis. The Journal of Immunology. 2010, 92-102). On the other side it is disclosed that methylation is connected with marker expression (Hamerman, Page, Pullen. Distinct methylation states of the CD8β gene in peripheral T cells and Intraepithelial Lymphocytes. The Journal of Immunology 1997, P1240-1246; Janson P. C. J. et al. Profiling of CD4+ T cells with epigenetic immune lineage analysis. The Journal of Immunology. 2010. 92-102; Melvin et al. Hypomethylation in IFN-Gamma Gen correlates with expression of IFN-G, including CD8 cells., Eur J Immunol. 1995 February; 25(2):426-30; Landolfi M M et al. CD2−CD4−CD8− lymph node T lymphocytes in MRL lpr/lpr mice are derived from a CD2+CD4+CD8+ thymic precursor J Immunol. 1993 Jul. 15; 151(2):1086-96; and Carbone A M et al. Demethylation in CD8 suggests that CD4+ derives from CD8+ cells. Role of methylation pattern during cell development. Science. 1988 Nov. 25; 242(4882):1174-6).
In view of the above mentioned demands in both clinical diagnostics and pharmaceutical research, a new method to provide a precise and comprehensive quantification of a variety of cell types in a sample is desired, in order to establish a more precise and thus markedly improved haemogram. Further objects and advantages will become apparent to the person of skill upon reading the present disclosure, and particularly the examples below.
In a first aspect thereof, this object is solved by the present invention by a method for producing an epigenetic haemogram, comprising the steps of epigenetically detecting blood cells in a biological sample, and quantifying said blood cells as detected using a normalization standard, wherein said normalization standard is a nucleic acid molecule comprising at least one marker-region being specific for each of the blood cells to be detected, and at least one control-region being cell-unspecific, wherein said regions are present in the same number of copies on said molecule and/or a natural blood cell sample of known composition.
Key and basis of the present invention is the use of a variety of different cell-type specific bisulfite-convertible DNA marker. These markers are employed for the identification and quantification of a single blood and immune cell types.
In principle, it was previously shown how a quantification of cell types and blood cell counting based on known epigenetic procedures is performed ((Wiezcorek et al., Cancer Res. 2009 Jan. 15; 69(2):599-608, Sehouli et al. Epigenetics. 2011 February; 6(2):236-46.). In brief, either a cell type specifically modified gene region is specifically (amplified and) counted and hence quantitated along with the opposite species of the cell type specific gene region. To provide for an independent quantification, these two measurements are then put into relation to provide the percentile part of the cell type in the given (blood) sample:Copy number of bisulfite convertible DNA of cell-type specific genomic region/(copy number of bisulfite convertible DNA of cell-type specific genomic region)+(Copy number of non-bisulfite convertible DNA of cell-type specific genomic region)=% cell type
Alternatively, the number of copies of bisulfite convertible DNA of a cell-type specific gene region is measured and divided by the copy number of bisulfite-convertible DNA of a cell-type non-specific gene region in the given sample. The latter can be determined by measuring all DNA copies using a completely bisulfite-convertible, cell-unspecific gene region or a region that is known to be uniformly bisulfite-unconvertible or bisulfite-convertible in all cell types.Copy number of bisulfite convertible DNA of cell-type specific genomic region/Copy number of a bisulfite convertible DNA of cell-type unspecific genomic region=% cell type
Hence, when a single specific bisulfite-convertible genomic marker is known, the previously established system allows the relative (percentile (%)) quantification of any one cell type in a given sample. For this, any given standardization of copy numbers or copy equivalents can be used. The resulting percentile share of the cell type in question correlates with the share of cells measured with a different method. Here, “correlating” means that—according to Spearman correlation—the lowest share measured by the epigenetic technology corresponds to the lowest share measured by—for example—flow cytometry. Such system has been shown to be very stable, technically robust and reliable. Therefore, whenever there is a highly cell-specific bisulfite convertible DNA marker achieved, in theory it should be possible to make an accurate and precise determination of the amount of those cells that own the specific bisulfite convertible genomic marker region.
It is known that the efficiency and performance of Real time (RT-)PCR systems differ depending on the RT-PCR components, including primers, probes, and the purity of DNA. Therefore, standards are employed in order to account for the problem to know at which Cp (crossing point) or Ct (threshold cycle) value a given (known) amount of standard DNA can be detected. A dilution series of said standard DNA gives a standard curve, and allows for the normalization of differently performing/efficient RT-PCR systems. Since the quantification is performed on an equivalent system, differences in performance are normalized. However, the problem addressed concerns an (RT-)PCR that is performed on DNA aiming at the detection of biologically and/or chemically altered DNA. The complexity of this biologically and/or chemically altered DNA differs from normal/natural genomic DNA (starting by the simple fact that the complexity of the DNA molecules differ, since a plasmid consists of double stranded DNA of four bases (CTGA), whereas genomic DNA consists of double stranded five bases (CTGACm), and bisulfite converted DNA merely consists of only three single stranded bases (TGA)). Thus, the efficiency of amplification differs between the target DNA (i.e., human chromosomal genomic or bisulfite-converted DNA) and the standard DNA, if the standard is a plasmid or genomic DNA, but more importantly, the “amplification efficiency difference” between (plasmid) standard and the target DNA differs from amplification target to amplification target. (i.e., primer pair, probe etc.). This leads to a number of observations, when qPCR is performed on bisulfite treated and amplified DNA, such as, for example:
When different blood cells in a sample shall be measured, independently of method as used, the total cell number should be equivalent. However, in a given sample that is equally distributed for the performance of different qPCR-assays, despite the use of individual standards for each reaction the total number of copies as detected is different. This leads to the following problem (here shown with CD3 as an example) in case of (e.g.) blood samples that are measured using different RT-PCR systems:
TABLE 1Calculation of overall DNA copy numbers and quantitative cell content followingepigenetic qPCR using bisulfite-treated, amplified DNA of a blood sample. (CP) crossing point, (CN − BC) copy numbers bisulfite converted CD3+ marker DNA region, (CN − NBC) copy numbers non-bisulfite converted CD3+ marker DNA region, (CN − GAPDH) copy numbers bisulfite converted GAPDH marker DNA region.PCR for CD3+ bisulfite PCR for CD3+ non-bisulfite converted DNAconverted DNAcopycopynumbersnumbersacc. tomean copyacc. tomean copysampleplasmidnumberssampleplasmidnumbersIDCPstandard(CN − BC)IDCPstandard(CN − NBC)WBL0231.81114.00264.67WBL0227.011410.001413.33WBL0230.31323.00WBL0226.991430.00WBL0230.17357.00WBL0227.031400.00WBL0329.21692.00693.00WBL0327.461070.001053.33WBL0329.3 650.00WBL0327.531020.00WBL0329.12737.00WBL0327.451070.00PCR for GAPDH bisulfite converted DNAcopynumbersacc. tomean copyCalculation overall DNA copy numberssampleplasmidnumberssampleCN − BC + CN − NBCCN − GAPDHIDCPstandard(CN − GAPDH)WBL0216781420WBL0227.3 1520.001420.00WBL031746.331383.33WBL0227.481350.00WBL0227.441390.00WBL0327.471360.001383.33WBL0327.431390.00WBL0327.421400.00Calculation of % CD3+ cell contentCN − BC × 100CN − BC × 100sample(CN − BC + CN − NBC)CN − GAPDHWBL0215.8%  18%WBL0336.6%50.1%
As indicated in Table 1, calculated overall CD3+ DNA copy numbers differ between the two used standardization systems: bisulfite-converted vs. non-converted DNA and bisulfite-converted CD3+ marker region to bisulfite-converted GAPDH (overall cell) marker region. For the first blood sample (WBL02), number of CD3+ DNA copies calculated via number of GAPDH bisulfite converted DNA (1420 copies) is smaller than calculated via bisulfite converted added to non-bisulfite converted CD3+ DNA copy numbers (1678 copies). For the second sample (WBL03) the situation is similar. Differences become more obvious when using these calculated copy numbers for quantification of CD3+ cells within these two blood samples. For sample WBL02, quantification via bisulfite converted to non-converted DNA copy numbers results in 36.6% CD3+ cells, whereas quantification via bisulfite converted CD3+ DNA copy numbers to bisulfite converted GAPDH DNA copy numbers results in 50.1% CD3+ cells. Both results and methods differ strongly.
As mentioned, even if normalization on a bisulfite-converted plasmid standard is performed, the different performances/efficiencies of the different assays do not lead to the same copy number.
This problem becomes particularly apparent, when purified cell types are measured with “their” specific epigenetic cell type markers, and compared to the total amount of cells in the sample (as measured by an cell-type unspecific marker (GAPDH)) as well as measured by non-bisulfite convertible DNA of a cell-type specific marker region (here FOXP3).
TABLE 2Assessment of quantitative amount of regulatory T cell (Treg)within two samples of purified Tregs. DNA was isolated, bisulfitetreated and relative amount of bisulfite converted and non-converted DNA assessed via qPCR. Copy numbers of bisulfiteconverted DNA in cell-specific FOXP3 regions were set in relationto copy numbers of bisulfite converted DNA in cell-unspecificGAPDH region as well as to bisulfite non-converted DNA in cell-type specific FOXP3 regions to obtain quantitative number of Tregs.(CP) crossing point), (CN-BC) copy numbers bisulfite convertedcell-type specific FOXP3 DNA region, (CN-NBC) copy numbersnon-bisulfite converted cell-type specific FOXP3 DNA region(CN-GAPDH) copy numbers bisulfite converted GAPDH DNA region.PCR for FOXP3 bisulfite converted DNAmean copy numberssampleacc. to plasmidIDCPstandard (CN-BC)8827.522366.69529.73513.34PCR for FOXP3 non-bisulfite converted DNAmean copy numberssampleacc. to plasmidIDCPstandard (CN-NBC)8832.8272.549535.4810.92PCR for GAPDH bisulfite converted DNAmean copy numberssampleacc. to plasmidIDCPstandard (CN-GAPDH)8826.62320.009528.91483.67Calculation of % Treg cell contentsampleCN-BC × 100CN-BC × 100ID(CN-BC + CN-NBC)CN-GAPDH8897.03%102%9597.92%106%
As can be seen from table 2, again, results for both of the quantification methods differ strongly (97% vs. 102% and 97% vs. 106%).
Finally, when different cell fractions, e.g. blood leukocytes, are measured that, when added up, should make up all cells in the sample as present, the above problem makes it impossible to provide for a correct “complete blood count”. As an example for this, for two blood samples the leukocytes were quantified (Table 3, sample 04 and sample 08). Here, the term leukocytes summarize all the five types of white blood cells: granulocytes, monocytes, B-lympocytes, natural killer cells, and CD3+ T-lymphocytes. Accordingly, it was expected that the single cell counts sum up to 100%, representing a (complete) leukocytogram. However, when using epigenetic qPCR analyses, this is often not the case (see Table 3). The sum of individual quantities of leukocytes often differs from 100%.
TABLE 3Assessment of the quantitative cell composition of two blood samples.DNA was isolated, bisulfite treated and relative amount of bisulfiteconverted DNA assessed via qPCR. Copy numbers of bisulfite convertedDNA in cell-specific regions were set in relation to bisulfite convertedcopy numbers of the cell-unspecific DNA region for GAPDH to obtainquantitative number of leukocytes. (CN-BC) copy numbers bisulfiteconverted cell-type specific marker DNA region, (CN-GAPDH)copy numbers bisulfite converted GAPDH marker DNA region.Calculation of Leukocytogram (% of cells)sample04sample08CN-BC × 100CN-BC × 100cell typeCN-GAPDHCN-GAPDHgranulozytes79.74%81.29%monozytes7.94%11.05%B cells1.63%1.68%natural killer cells2.74%2.04%T cells23.25%22.09%Sum:115.3118.15
When summarizing the above mentioned problems of epigenetic cell quantification, a precise blood counting tool provides the following:
1. allows for the assessment of a precise, comprehensive blood and immune cell count,
2. overcomes differences in assay performance and/or efficiency between standards as used and the biological sample to be analyzed,
3. is independent of membrane integrity of cells to be counted (intact or non-intact cells), and
4. is independent of type of cell containing sample (fresh, frozen, embedded, stored, fluids, solid tissues).
The present invention provides such a tool, and respective methods. According to the present invention, assessing the epigenetic haemogram comprises measurement of the absolute amount of cells by normalization of qPCR results on a bisulfite-unconverted or -converted normalization standard. The normalization standards consist of a nucleic acid molecule comprising at least one marker-region being specific for each of the blood cells to be detected, and at least one control-region being cell-unspecific, wherein said regions are present in the same number of copies on said molecule and/or a natural blood cell sample of known composition.
In a first step of a preferred embodiment of the method, qPCR assay-specific correction factors are determined to achieve normalization and comparability of all qPCR assays as well as to correct for differences in assay efficiencies. In a second step, DNA of biological sample is isolated, purified and bisulfite treated. This is followed by qPCR specific for bisulfite-converted cell-type specific and/or cell-type unspecific genomic marker regions. The qPCR amplification results are then normalized with said normalization standard, which represents the relative amount of copies of marker DNA, and therefore the relative amount of specific cells. The normalization standard contains bisulfite-converted genomic marker regions or contains native, bisulfite-unconverted, marker regions. Before starting the qPCR, in the latter case the nucleic acid will be bisulfite treated in parallel to the biological sample as analyzed is treated. In a next step, following qPCR, the normalized relative amount of copies of marker DNA is corrected by an assay specific correction factor as described herein in order to correct for differences in assay efficiencies indicating the absolute amount of cells.
The present method allows for a quantification of non-intact but also intact blood cells in biological samples, such as, for example, dried, frozen, embedded, stored as well as fresh body fluids, dried blood spots, blood clots and tissue samples. The sample does not contain purified or enriched cells. Furthermore, the method of the present invention provides for a blood count, wherein the identity and quantity of cells is based on a clear yes/no information on the genomic level that is independent from protein expression levels.
The present invention thus provides a blood and/or immune cell count to be used as an analytical and diagnostic tool for medical use and as a basis for decisions in therapy.
Preferred is a method according to the present invention, furthermore comprising the step of obtaining a comprehensive blood picture, based on said detecting and quantifying. The blood cell count thus identifies the comprehensive picture of the cellular composition based on a number of epigenetic parameters. The combination of these epigenetic parameters is used to identify the cell composition of a blood or tissue sample, i.e. an epigenetic haemogram, and said epigenetic haemogram is provided based on the analysis of the bisulfite convertibility of cell-specific genomic regions.
Preferably, said epigenetic haemogram resembles a leukocytogram and/or a T-lymphocytogram and/or a granulocytogram and/or a monocytogram and/or a B-lymphocytogram and/or a NK cytogram.
Preferably, the method according to the present invention furthermore comprises the use of a bisulfite-unconverted or -converted normalization standard for the normalization, e.g. of the qPCR results. The term “bisulfite-unconverted” normalization standard encompasses natural DNA molecules containing the original/primary biologic modifications, such as formylation, carboxylation, methylation, or hydroxymethylation and that is not bisulfite-treated, and therefore bisulfite-unconverted. The term “bisulfite-converted” normalization standard encompasses DNA molecules containing (genomic) marker sequences corresponding to already bisulfite-converted cell-type specific and unspecific marker regions.
The bisulfite-unconverted or bisulfite-converted nucleic acid molecule is preferably selected from a plasmid, a yeast artificial chromosome (YAC), human artificial chromosome (HAC), P1-derived artificial chromosome (PAC), a bacterial artificial chromosome (BAC), and a PCR-product. Bisulfite-converted normalization standard is a plasmid, yeast artificial chromosomes (YAC), human artificial chromosome (HAC), P1-derived artificial chromosome (PAC), bacterial artificial chromosome (BAC) or a PCR-product.
The natural blood cell sample preferably is a blood sample of known cellular composition, and/or of known composition of blood cell types, and is preferably produced in advance, i.e. the amount and number blood cell types as combined is pre-determined.
In a preferred embodiment of the method according to the invention, the normalization standard, i.e. the plasmid, YAC, HAC, PAC, BAC, and PCR-product, contains cell-specific and unspecific genomic marker regions (to be analyzed in accordance with the epigenetic haemogram) in the same known number of copies on said molecule. In one embodiment, each of these standards is a single molecule containing the same number of all cell-type specific and unspecific genomic marker regions of interest in the epigenetic haemogram to be established. The natural blood cell sample (preferably mammalian, such as human) used as the bisulfite-unconverted normalization standard contains cells in a known composition and quantity, whereby cells can be pre-purified and pre-mixed to obtain a sample of known composition, that is also pre-determined.
During analytical processing, the bisulfite-unconverted normalization standard is bisulfite-treated in parallel and in the same fashion than the bisulfite treatment of the biological sample to be analyzed.
Then, qPCR on the unknown biological sample as well as on the (now) bisulfite-treated bisulfite-unconverted normalization standard is performed using specific primers that help to detect cell-type specific or unspecific bisulfite-converted genomic regions. In contrast, the bisulfite-converted normalization standard will (obviously) not be bisulfite-treated, as it already contains specific marker sequences that correspond to bisulfite-converted marker sequences recognized by qPCR primers that are specific for bisulfite-converted genomic regions.
In a preferred embodiment, the normalization standard comprises a predetermined amount of blood cells of the types to be detected and analyzed according to the haemogram. Preferably, a normalization standard is used consisting of a defined copy number and same stoichiometric amount of specific cells and/or of cell-type specific and/or cell-type unspecific marker regions. Preferred is a single plasmid containing the same copy number and/or stoichiometric amount of cell-type specific and/or cell-type unspecific marker regions for all cell types of interest for the haemogram.
A preferred embodiment of the method according to the invention furthermore comprises the step of correcting said epigenetic haemogram as produced with an assay specific correction factor. Said assay-specific correction factor (for the cells as detected and analyzed) is determined by comparing the known quantitative amount of cells in said mammalian natural cell sample as provided with the relative amount of copy numbers of bisulfite-converted cell-type specific marker DNA of said mammalian natural cell sample assessed by the qPCR using the normalization standard. Using this approach, the present method allows for an accurate quantification of cells, as any assay-specific variations that may have occurred are taken into account. Depending from the kind of normalization standard as used, the assay specific correction factors can differ. The more the normalization standard and its analytical processing are adapted to the biological sample and its processing, the more the assay specific correction factors will approach 1, or even can be neglected. In a preferred embodiment, a bisulfite-unconverted normalization standard is used as it resembles the complexity and impureness of natural cell samples, and therefore the qPCR efficiency between a biological sample and standard should be aligned. Most preferred is the use of a mammalian natural cell sample of known cell composition and quantity as described herein.
The method according to the present invention then comprises the step of determining the relative amount (of copies) of cell-type specific and unspecific DNA within the biological sample of unknown composition. This is achieved by qPCR on isolated, purified and bisulfite-converted DNA of said biological sample under the use of primers specific for bisulfite-converted cell-type specific and unspecific DNA marker sequences. qPCR amplification results for all target cell types are the normalized on said bisulfite-unconverted or converted standard indicating the relative amount of target cells. According to standards and assays used, specific assay correction factors are applied on relative amount of target cells to receive the absolute amount and percentage of the content of cells according to said haemogram as established. Thereby, the absolute, comprehensive cellular composition in said biological sample is determined. Depending from the normalization standard used, the assay correction factor differs from 1, or is approximately 1, and then can be neglected. Other methods for determining the relative amount (of copies) of cell-type specific and unspecific DNA comprise a method selected from specific enzymatic digests or dye exclusion technologies, bisulfite sequencing, next generation sequencing, nanopore sequencing, single molecule real-time sequencing, analyses of epigenetic modifications in promoter regions, using primers specific for bisulfite-converted DNA, using blocking oligonucleotides specific for bisulfite-converted DNA, using fluorescence-labeled, quenched oligonucleotide probes, using primers for single nucleotide primer extension specific for bisulfite-converted DNA, digital or quantitative PCR analysis, and specific selective (nucleic acid and/or chromatin) precipitation.
Preferred is a method according to the present invention, wherein the determination of the relative amount of target cells is based on comparing the amounts of copies of said bisulfite-converted cell-specific regions as determined with the amounts of copies of the bisulfite-converted regions that are unspecific for a cell-type as determined, thereby identifying the relative amount of a specific cell type in relation to all cells present in the sample.
In one embodiment according to the present invention, the relative amount of target cells is determined based on comparing the amounts of copies of said bisulfite-converted cell-specific regions as determined with the amounts of copies of bisulfite-unconverted cell-specific regions as determined, thereby identifying the relative amount of target cells in relation all other cells present in the sample.
In a preferred embodiment of the method according to the invention, further a knowledge base comprising information about cell-specific assay-correction factors estimated/calculated during previous assessments of epigenetic assays is generated. These values may be advantageously used in order to select particularly suitable normalization standards.
In a particularly preferred embodiment of the method according to the present invention, cell-type marker regions are detected that discriminate a specific cell type and/or at least one specific subpopulation of cells from other cells of a leukocytogram, a T-lymphocytogram, a granulocytogram, a monocytogram, a B-lymphocytogram and/or a NK-cytogram. Preferably, a) the leukocytogram consists of T-lymphocytes, natural killer cells, B-lymphocytes, monocytes and/or granulocytes, b) the T-lymphocytogram consists of CD3+CD4+, CD3+CD8+, CD8−CD4−, and/or CD8+CD4+ c) the granulocytogram consists of basophilic, eosinophilic, neutrophilicgranulocytes, and/or granulocytic myeloid-derived suppressor cells, d) the monocytogram consists of CD14+ monocytes, CD14− monocytes, macrophages, monocytic myeloid-derived suppressor cells, plasmacytoid dendritic cells, myeloid dendritic cells, and/or overall dendritic cells, e) the B-lymphocytogram consists of naïve B cells, pre-B cells, memory B cells, transitional B cells and/or immature B cells, and f) the NK cytogram consists of CD56dim and/or CD56bright NK cells.
Preferably, within the haemogram as determined sub-haemograms (or subpopulations) can be determined. Preferred is a T-helper-cytogram comprising, e.g., Th1, Th2, Th9, Th17, Th19, Th 21, Th22, Tfh, CD4+ natural killer cells (NKT), naïve CD4+, memory CD4+, effector CD4+ cells, and/or CD4+ regulatory T cells, or a T-cytotoxogram comprising, e.g., naïve CD8+, effector CD8+, memory CD8+, CD8+ natural killer cells (NKT), and/or CD8+ regulatory T cells. Furthermore, sub-populations of monocytes can be determined, comprising classical monocytes (CD14−), intermediate monocytes (CD14+) and/or non-classical monocytes (CD14++) or a dendritogram comprising myeloid dendritic cells, and plasmacytoid dendritic cells. Future scientific studies may discover and identify yet unknown blood cells and leukocyte subgroups and may will assign new functions to certain blood cells and/or will assign known blood cells to different leukocyte subpopulations.
To determine the relative amount of bisulfite-convertible and/or non-bisulfite convertible DNA or nucleic acid comprises a method selected from specific enzymatic digests or dye exclusion technologies, bisulfite sequencing, next generation sequencing, nanopore sequencing, single molecule realtime sequencing, analyses of epigenetic modifications in promoter regions, using primers specific for bisulfite-converted DNA, using blocking oligonucleotides specific for bisulfite-converted DNA, using fluorescence-labeled, quenched oligonucleotide probes, using primers for single nucleotide primer extension specific for bisulfite-converted DNA, digital or quantitative PCR analysis, and specific selective (nucleic acid and/or chromatin) precipitation.
Further preferred is a method according to the present invention, wherein said normalization standard is bisulfite-unconverted and contains at least one bisulfite-convertible CpG position.
Further preferred is a method according to the present invention, wherein said quantifying of cell types in said biological sample is based on the normalization of the relative amount of cell-type specific and unspecific chromatin using the bisulfite-unconverted normalization standard or using the bisulfite-converted normalization standard.
Even further preferred is a method according to the present invention, wherein said normalization using the bisulfite-unconverted normalization standard is indicative for the absolute amount and/or percentage of content of cells within said biological sample
Even further preferred is a method according to the present invention, wherein said biological sample is a sample of unknown cellular composition.
The biological sample as analyzed in the context of the present invention is any sample that contains cells to be analyzed, i.e. cells of the blood and/or immune system, such as cells of a leukocytogram, selected from T-lymphocytes, natural killer cells, B lymphocytes, monocytes, and/or granulocytes, and combinations thereof; a T-lymphocytogram, selected from CD3+CD4+, CD4+ memory, CD4+ effector cells, CD4+ naïve, CD3+CD8+, CD8+ memory, CD8+ effector cells, CD8+ naïve, CD3+CD8− CD4−, CD3+CD8+CD4+, NKT cells, iTreg, Treg, Tfh, Th1, Th2, TH9, Th17, Th19, Th21, Th22, memory and/or effector T helper cells, and combinations thereof, a granulocytogram, selected from basophilic, eosinophilic, neutrophilic, overall neutrophil granulocytes, and/or granulocytic myeloid-derived suppressor cells, and combinations thereof, a monocytogram, selected from CD14+ monocytes, CD14- monocyes, macrophages, plasmacytoid dendritic cells, monocytic myeloid-derived suppressor cells, intermediate monocyets, classical monocytes, non-classical monocytes, and/or overall dendritic cells, and combinations thereof, a B-lymphocytogram, selected from naïve B cells, pre B cells, memory B cells, transitional B cells and/or immature B cells, and combinations thereof, and a NK cytogram, selected from CD56dim and/or CD56bright NK cells.
The term “cell-specific region(s)” herein shall mean genetic regions in the genome of cells and/or nucleic acids that are selected to discriminate on an epigenetic level one cell type and/or subpopulations of cells from all other cell types and/or subpopulations of cells. These regions include the genes of certain markers (such as, for example, certain protein markers), such as 5′ untranslated regions, promoter regions, introns, exons, intron/exon borders, 3′ regions, CpG islands, and in particular include specific regions as amplified after bisulfite treatment (amplicons) that are “informative” about the one cell type and/or subpopulations of cells. Examples for these cell-specific regions are known from the literature, such as, for example, the gene CD3 γ, δ and ε (WO 2010/069499); the granulysine gene (WO 2010/125106); the CCR6 gene (WO 2011/135088); the FOXP3 gene (WO 2004/050706 and Wieczorek et al. Quantitative DNA methylation analysis of FOXP3 as a new method for counting regulatory T cells in peripheral blood and solid tissue. Cancer Res. 2009 Jan. 15; 69(2):599-608.)
Cell-specific marker region usually are DNA regions that contain single CpGs or CpG islands that are bisulfite-convertible only in a specific cell type and therefore indicative for the specific cell type. Additionally, these cell-specific marker regions discriminate one cell type from all other blood cells as well as other tissue cells.
According to the present invention, cells of the epigenetic haemogram are identified and quantified by analyzing the bisulfite convertibility of at least on CpG position in said cell-specific genomic regions.
Thus, preferred is a method according to the present invention, wherein a bisulfite conversion of at least one CpG position within a region as listed in the following table 4 is indicative for the respective blood cell type as listed in said table. These are e.g. the following genomic marker regions for the given cell types:
TABLE 4cell-specific genomic regionsSEQ IDDis-cov-eryfragcyto-ment/Gran-toxicSEQMarker-ENSEMBLulo-Mono-CD4+T-B-NK-NKIDPosIDTargetIDSYMBOLAccession(ENSG #)cytescytescellscellscellscellsT'sROI 1NK_nm1cg08766149GZMBNM_004131001004530.910.900.870.890.570.13 1/2 2NK_nm2cg22917487CX3CR1NM_001337001683290.920.920.940.920.570.13 3/4 3NK_nm3cg12445208ZNF583NM_152478001984400.770.830.760.640.730.180.54 5/6 4NK_nm4cg02196805CSF2NM_000758001644000.780.780.500.600.770.220.52 7/8 5NK_nm5cg23617121OSBPL5NT_009237000217620.950.950.920.890.850.220.81 9/10 6NK_nm6cg20697204FLJ40172NM_173649002396050.780.890.910.830.730.23 11/12 7NK_nm7cg11801011SHANK1NM_016148001616810.680.620.640.720.560.26 13/14 8NK_nm8cg07873128OSBPL5NT_009237000217620.930.940.930.930.600.27 15/16 9NK_nm9cg03368758LDB2NM_001290001697440.740.780.750.710.670.270.68 17/18 10NK_nm10cg00515905EPS8L3NM_024526001987580.920.930.920.940.840.29 19/20 11NK_nm11cg22228134GZMHNM_033423001004500.830.900.900.890.530.30 21/22 12NK_nm12cg26379475SH2D1BNM_053282001985740.790.790.640.640.590.320.61 23/24 13NK_nm13cg04384208FCGR3ANM_000569002037470.840.870.820.830.710.32 25/26 14NK_nm14cg00453258FAM26CNM_001001412001859330.710.710.850.820.920.33 27/28 15NK_nm15cg06827976FGRNM_005248000009380.780.830.880.800.78 0.350.60 29/30 16NK_nm16cg12491710LIM2NM_030657001053700.950.940.930.930.860.36 31/32 17NK_nm17cg18250832NMUR1NM_006056001715960.760.720.780.740.770.38 33/34 18NK_nm18cg15544721PPP1R9AXM_371933001585280.640.760.850.880.530.38 35/36 19NK_nm19cg25943702BRD1NM_014577001004250.800.840.800.780.730.380.71 37/38 20NK_nm20cg04230060SUSD1NM_022486001068680.690.690.910.870.710.390.84 39/40 21NK_nm21cg06229674ARP10NM_181773001002980.940.950.930.920.500.40 41/42 22NK_nm22cg14701962C1orf111NM_182581001717220.810.850.790.770.740.410.69 43/44 23NK_nm23cg16522484C14orf49NM_152592001764380.720.800.740.740.530.42 45/46 24NK_nm24cg26738080TNNC1NM_003280001148540.840.760.870.860.660.42 47/48 25NK_nm25cg13525683TIAF1NM_004740002219950.810.830.780.770.750.420.75 49/50 26NK_nm26cg23352030PRIC285NM_033405001305890.850.820.950.940.900.43 51/52 27NK_nm27cg23282949RENBPNM_002910001020320.720.760.910.850.860440.81 53/54 28NK_nm28cg00491404EPS8L3NM_024526001987580.880.830.880.870.790.45 55/56 29NK_nm29cg25903122MGC2747NM_024104002140460.870.920.920.890.680.48 57/58 30NK_nm30cg22202141FCGR3ANM_000569002037470.900.870.880.890.580.48 59/60 31NK_nm3lcg11094938ATP2A1NM_173201001962960.910.850.900.900.920.49 61/62 32NK_nm32cg23580000ADCY7NM_001114001212810.800.810.960.940.920.49 63/64 33NK_m1cg12167564LYSTNM_000081001436690.300.130.470.500.360.680.37 65/66 34NK_m2cg18881723SLAMF1NM_003037001170900.030.030.030.050.080.66 67/68 35NK_m3cg18096388PDCD1NM_005018001883890.410.500.110.200.360.650.25 69/70 36NK_m5cg27016307HRCNM_002152001305280.460.440.210.330.300.560.11 71/72 37NK_m6cg18818531FOSL1NM_005438001755920.400.420.170.170.370.560.25 73/74 38NK_m7cg27067618CYP4F3NM_000896001865290.150.290.380.410.400.550.23 75/76 39NK_m8cg04790129ITGB2NM_000211001602550.130.240.350.400.130.540.39 77/78 40NK_m9cg25944100MS4A3NM_006138001495160.100.200.460.410.400.540.38 79/80 41NK_m10cg09076123NCF2NM_000433001167010.030.070.280.310.240.530.13 81/82 42NK_m11cg05275752GALMNM_138801001438910.190.180.290.440.300.520.33 83/84 43NK_m12cg19030554NME3NM_002513001030240.150.360.290.340.490.51 85/86 44NKT_n1cg02833725ISG20L2NM_030980001433190.810.860.520.550.630.880.15 87/88 45NKT_n2cg06736444SRRM2NM_016333001679780.840.870.590.590.530.860.25 89/90 46NKT_n3cg14862827SUSD1NM_022486001068680.620.620.590.710.550.650.17 91/92 47NKT_n4cg06154597MGC4618NM_032326001274190.820.840.610.580.830.620.27 93/94 48NKT_n5cg17267907DEFA1NM_004084002398390.800.830.710.540.770.560.32 95/96 49NKT_n6cg15210427CST9LNM_080610001014350.820.880.560.630.620.790.34 97/98  50NKT_n7cg08603768WNT8ANM_031933000614920.810.810.540.510.590.660.28 99/100 51NKT_n8cg14366490TXNL6NM_138454001717730.810.810.510.560.580.740.30101/102 52NKT_n9cg25827666NTRK1NM_001007792001984000.860.860.630.640.820.570.36103/104 53NKT_n10cg10624445CNGB1NM_001297000707290.830.860.580.580.640.820.35105/106 54NKT_n11cg01605984SURF5NM_181491001482970.770.860.510.550.620.810.32107/108 55NKT_n12cg20661303LEFTY2NM_003240001437680.740.750.590.650.770.860.39109/110 56NKT_n13cg12240237WBSCR23NM_025042000067040.840.860.510.530.600.770.36111/112 57NKT_n14cg14375111TMEM43NM_024334001708760.920.950.620.610.650.890.45113/114 58NKT_n15cg19464252FBS1NM_022452001568600.860.900.620.540.550.830.40115/116 59NKT_n16cg14076161PRB4NM_002723002306570.820.780.520.530.640.760.36117/118 60NKT_n17cg10848367SCGB1D2NM_006551001249350.780.780.550.600.560.680.34119/120 61NKT_n18cg00626119NTRK1NM_001007792001984000.790.820.590.610.800.570.38121/122 62NKT_n19cg13881341FUT1NM_000148001749510.880.860.650.670.690.800.45123/124 63NKT_n20cg10779183ELA3ANM_005747001427890.840.850.580.640.700.720.42125/126 64NKT_m13cg00754253HRASLS5NM_054108001680040.090.370.330.400.440.500.70127/128 65NKT_m12cg13492227FGF11NM_004112001619580.170.200.500.450.310.380.69129/130 66NKT_m1cg07233761ESM1NM_007036001642830.090.080.370.380.050.160.68131/132 67NKT_m2cg03973663LYNNM_002350002540870.120.110.390.420.240.140.66133/134 68NKT_m6cg09082287DNAJC6NM_014787001166750.150.150.410.350.300.240.66135/136 69NKT_m7cg14289511FLJ45256NM_207448002243100.090.100.450.400.230.120.62137/138 70NKT_m8cg03682712LOXL1NM_005576001290380.040.120.470.460.230.100.62139/140 71NKT_m3cg16907566COL14A1NM_021110001879550.140.140.280.350.190.130.62141/142 72NKT_m5cg22854223CD82NM_002231000851170.040.040.420.430.130.190.61143/144 73NKT_m15cg01305421IGF1NM_000618000174270.070.060.420.470.240.360.61145/146 74NKT_m17cg05989054GAMTNM_000156001300050.080.080.440.370.110.170.55147/148 75NKT_m4cg26482939GNA15NM_002068000605580.060.040.240.280.090.100.55149/150 76NKT_m16cg20876010CACHD1NM_020925001589660.120.120.310.280.200.180.54151/152 77NKT_m19cg15526708TGFBR1NM_004612001067990.150.130.310.360.130.150.54153/154 78NKT_m14cg22799850FBXL13NM_145032001610400.070.070.310.480.070.180.54155/156 79NKT_m18cg13105904KIAA0323NM_015299001004410.130.200.130.280.160.300.53157/158 80NKT_m20cg22268231SPIBNM_003121002694040.130.080.360.450.060.140.53159/160 81NKT_m10cg10784030INPP5BNM_005540002040840.080.080.230.170.110.130.49161/162 82NKT_m11cg19766460C21orf128NM_152507001843850.040.040.060.240.040.060.44163/164 83B_nm1cg00226923FGD2NM_173558001461920.930.960.950.960.100.95165/166 84B_nm2cg03860768BLKNM_001715001365730.830.880.870.860.1I0.82167/168 85B_nm3cg16280667BLR1NM_001716001606830.880.870.870.900.140.89169/170 86B_nm4cg14127336TCL1ANM_021966001007210.920.920.920.920.140.93171/172 87B_nm5cg22679120SNX8NM_013321001062660.640.650.590.630.150.720.64173/174 88B_nm6cg16698623MGMTNT_008818001704300.950.940.960.970.150.93175/176 89B_nm7cg10115873DNAJB7NM_145174001724040.680.800.800.750.160.79177/178 90B_nm8cg27394566PLD4NM_138790001664280.720.560.880.890.160.85179/180 91B_nm9cg14102807CD19NM_001770001774550.880.900.920.930.160.89181/182 92B_nm10cg17399166CD1DNM_001766001584730.890.810.880.880.170.87183/184 93B_nm11cg22194129CLEC4CNM_130441001981780.850.880.900.920.170.85185/186 94B_nm12cg15121304——001975490.890.850.730.800.180.64187/188 95B_nm13cg18979762EGLN1NM_022051001357660.800.840.830.810.190.72189/190 96B_nm14cg03221619FCER2NM_002002001049210.800.730.750.710.190.760.59191/192 97B_nm15cg07597976CD19NM_001770001774550.720.630.630.680.200.600.58193/194 98B_nm16cg00126698BTKNM_000061000106710.630.620.860.770.200.760.81195/196 99B_nm17cg16098726GP9NM_000174001697040.710.820.920.910.200.87197/198100B_nm18cg02630207FLJ10379NM_018079000687840.730.740.710.680.210.650.67199/200/101B_nm19cg07790638LOC91431NM_138698—0.850.870.830.820.210.79201/202102B_nm20cg06667406AASSNM_005763000083110.850.840.850.830.220.81203/204103B_nm21cg26574610VPREB3NM_013378001282180.810.840.870.890.220.83205/206104B_nm22cg07426848S100A3NM_002960001880150.880.890.930.920.220.87207/208105B_nm23cg23984130—0.800.800.690.600.240.590.68209/210106B_nm24cg00113020LILRB4NM_006847001868180.780.770.770.690.240.560.73211/212107B_nm25cg25769980TLR6NM_006068001741300.900.900.870.870.250.81213/214108B_nm26cg16873863SLC22A18NM_183233001106280.590.610.750.760.250.740.71215/216109B_nm27cg22295573AQP4NM_001650001718850.870.900.870.890.250.84 217/218110B_nm28cg18075299C14orf54NM_173526001727170.840.890.850.890.260.86219/220111B_nm29cg02399455SRINM_198901000751420.880.870.900.860.260.78221/222112B_nm30cg10762615FBXW10NM_031456001719310.880.890.880.850.260.83223/224113B_nm31cg18557145CD72NM_001782001371010.800.870.890.910.260.830.84225/226114B_nm32cg00374717ARSGNM_014960001413370.900.910.850.850.260.85227/228115B_nm33cg19437319KIAA0196NM_014846001649610.900.890.860.840.260.87229/230116B_nm34cg14959707ZC3H7ANM_014153001222990.890.890.890.920.270.89231/232117B_nm35cg18152830TNFRSF13BNM_012452002405050.920.910.860.910.270.910.86233/234118B_nm36cg16593081DYX1C1NM_001033559002560610.910.920.890.880.280.87235/236119B_nm37cg26394380SFTPBNM_000542001688780.660.800.720.750.290.860.70237/238120B_nm38cg01909245LSP1NM_002339001305920.870.840:640.630.300.710.62239/240121B_nm39cg03270204DDR1NM_001954002045800.940.920.840.920.310.94241/242122B_nm40cg11042320PDGFRBNM_002609001137210.670.740.730.790.320.630.73243/244123B_nm41cg08251036MGAT5NM_002410001521270.830.870.830.790.320.680.83245/246124B_nm42cg05921699CD79ANM_001783001053690.840.810.800.670.320.700.78247/248125B_nm43cg25211252KCNMB3NM_014407001711210.860.830.830.830.340.830.80249/250126B_nm44cg21960110HBZNM_005332001306560.850.880.800.690.360.810.57251/252127B_m1cg27398547C14orf39NM_174978001790080.270.190.220.210.730.26253/254128B_m2cg22226839ATP2B4NM_001684000586680.160.180.250.230.720.34255/256129B_m3cg11997899DLX5NM_005221001058800.300.230.290.210.720.28257/258130B_m4cg19350340ASPMNM_018136000662790.140.130.160.200.720.22259/260131B_m5cg00049986C14orf10NM_017917000920200.170.110.210.170.700.20261/262132B_m6cg08360728GPATC3NM_022078001987460.280.310.330.240.690.31263/264133B_m7cg01222684TTC1NM_003314001133120.060.050.100.050.660.14265/266134B_m8cg00571634WDR5BNM_019069001969810.180.180.160.160.650.20267/268135B_m9cg18908499C1orf150NM_145278001692240.130.130.200.160.650.23269/270136B_m10cg00678539MNS1NM_018365001385870.120.130.190.180.600.15271/272137B_m11cg19756611DACH1NM_004392001656590.170.070.150.140.590.26273/274138B_m12cg23668631CAMKK1NM_032294000046600.100.220.360.440.580.440.35275/276139B_m13cg18967846CLDN12NM_012129001572240.140.140.160.100.580.24277/278140B_m14cg25482967MRPS10NM_018141000485440.120.090.140.110.560.17279/280141B_m15cg06751597SNAP23NM_003825000925310.070.070.110.090.560.07281/282142B_m16cg22285621SSH3NM_018276001728300.010.080.050.110.550.07283/284143B_m17cg17378989ERCC1NM_202001000120610.110.120.120.120.550.17285/286144B_m18cg03825921RAB4ANM_004578001681180.110.110.140.130.550.18287/288145B_m19cg11250058RAPH1NM_203365001731660.060.080.070.240.550.09289/290146B_m20cg03643709VPS18NM_020857001041420.180.130.190.100.540.22291/292147B_m21cg24641737DENND2DNM_024901001627770.030.030.040.030.540.05293/294148B_m22cg07732037MPHOSPH9NM_022782000518250.270.470.060.100.530.250.09295/296149B_m23cg05091653SP100NM_003113000670660.080.060.040.050.520.06297/298150B_m24cg16007628ZNF207NM_001032293000102440.130.150.170.150.520.180.22299/300151B_m25cg26954174CARD15NM_022162001672070.070.070.250.380.510.140.26301/302152B_m26cg01988129ADHFE1NM_144650001475760.160.180.200.220.500.200.19303/304153CD8_nm1cg18149207RORCNM_005060001433650.830.870.650.310.650.75305/306154CD8_nm2cg02519218CHFRNT_024477000726090.850.840.520.390.600.710.62307/308155CD8_nm3cg21755709C21orf124NM_032920001360140.660.710.650.430.630.640.66309/310156CD8_nm4cg24019564RUNX3NT_004610000206330.550.750.670.440.740.510.62311/312157CD8_nm5cg19700658UCP3NM_003356001755640.830.840.690.440.780.540.54313/314158CD8_nm6cg14027234CD248NM_020404001748070.830.830.820.450.710.82315/316159CD8_nm7cg03024246JRKLNM_003772001833400.690.780.770.450.530.630.67317/318160CD8_nm8cg21232015CHFRNT_024477000726090.870.880.610.460.630.810.73319/320161CD8_nm9cg12108912MGC10993NM_030577001441200.820.850.500.470.570.730.77321/322162CD8_nm10cg17505463GGT3NM_002058001974210.820.800.590.470.690.660.60323/324163CD8_nm11cg07232688LRRC39NM_144620001224770.710.750.720.470.590.500.64325/326164CD8_m1cg26848126CYSLTR1NM_006639001731980.120.040.180.720.260.10327/328165CD8_m3cg25511807MMP7NM_002423001376730.090.090.430.620.270.44329/330166CD8_m4cg16604516FBLN2NM_001004019 001635200.190.150.400.610.160.15331/332167CD8_m5cg23771929FREQNM_014286001071300.200.210.460.600.280.340.46333/334168CD8_m6cg20340242IL1R2NM_004633001155900.030.040.440.600.180.42335/336169CD8_m7cg09106999CDK2NM_001798001233740.070.080.480.600.290.29337/338170CD8_m8cg00516481PDE9ANM_002606001601910.190.180.490.570.180.320.46339/340171CD8_m9cg22054164ECE1NM_001397001172980.170.090.280.570.170.42341/342172CD8_m10cg06415153PITPNM2NM_020845000909750.190.120.390.560.220.40343/344173CD8_m11cg22778947FSD1NLNM_031919001067010.160.180.500.550.180.33345/346174CD8_m12cg03627896LOC283932NM_175901—0.340.410.310.530.210.310.12347/348175CD8_m13cg00833777ITGAMNM_000632001698960.080.090.420.520.250.16349/350176CD8_m14cg01356829IL12RB2NM_001559000819850.080.070.380.520.150.120.16351/352177CD8_m15cg18661868FESNM_002005001825110.080.110.340.510.290.13353/354178CD8_m16cg08899626LDB2NM_001290001697440.050.090.180.510.180.12355/356179CD8_m17cg14700707NOTCH4NM_004557002043010.050.050.390.500.140.350.30357/358180CD4_nm1cg03602500FLJ00060NM_033206001049700.860.850.260.520.660.87359/360181CD4_nm2cg16470760CD4NM_000616000106100.740.700.310.610.680.660.67361/362182CD4_nm3cg02989940ERAFNM_016633001698770.900.870.390.640.550.790.72363/364183CD4_nm4cg22972055UNC84ANM_025154001648280.910.930.420.640.500.89365/366184CD4_nm5cf29335340PTPN6NM_002831001116790.660.730.420.640.590.780.57367/368185CD4_nm6cg08214029CCL18NM_002988000060740.740.780.420.760.580.800.72369/370186CD4_nm7cg02385474PCNXL2NM_024938001357490.780.780.430.520.540.650.62371/372187CD4_nm8cg01782486ZBTB7BNM_015872001606850.750.820.440.880.520.810.83373/374188CD4_nm9cg25598083ACOT2NM_006821001196730.850.860.440.550.650.720.54375/376189CD4_nm10cg07327347AQP8NM_001169001033750.880.650.460.700.670.790.54377/378190CD4_nm11cg12703269PSTPIP1NM_003978001403680.820.820.460.610.800.840.59379/380191CD4_nm12cg23909633IL24NM_181339001628920.870.870.480.650.740.760.80381/382192CD4_nm13cg18669588PTK9LNM_007284002475960.800.830.500.640.750.770.62383/384193CD4_m1cg25655096GPR92NM_020400001845740.440.190.690.490.190.13385/386194CD4_m2cg05697976MLSTD1NM_018099000647630.090.140.620.500.420.360.48387/388195CD4_m3cg10521852EDG4NM_004720000645470.070.080.610.410.220.220.35389/390196CD4_m4cg08159444PNMA5NM_052926001988830.260.060.610.480.480.46391/392197CD4_m5cg00443307KLRG1NM_005810001391870.370.220.600.380.340.350.29393/394198CD4_m6cg04541607CRYBB1NM_001887001001220.060.100.590.460.140.47395/396199CD4_m7cg03085312RARANM_001024809001317590.160.150.590.380.180.170.39397/398200CD4_m8cg20764656GPX2NM_002083001761530.040.060.580.470.170.120.34399/400201CD4_m9cg07837085SLAMF7NM_021181000267510.060.070.570.350.270.07401/402202CD4_m10cg18440048ZNF70NM_021916001877920.120.170.560.210.130.200.34403/404203CD4_m11cg18752880C1QTNF3NM_181435000821960.060.290.560.460.460.150.21405/406204CD4_m12cg24576425GALNT5NM_014568001365420.110.080.560.460.260.240.46407/408205CD4_m13cg18055007DDAH2NM_013974002266340.110.080.550.210.150.130.14409/410206CD4_m14cg14913610KLRG1NM_005810001391870.060.070.550.430.180.160.17411/412207CD4_m15cg00563926TGFBR3NM_003243000697020.110.100.550.150.180.170.38413/414208CD4_m16cg05252264FCARNM_002000001864310.060.080.550.470.210.38415/416209CD4_m17cg16465939KCNQ1NT_009237000539180.050.050.540.220.280.11417/418210CD4_m18cg19963522PIP3-ENM_015553000747060.090.110.54.0.380.190.320.46419/420211CD4_m19cg05512099PLEKHF1NM_024310001662890.150.190.540.420.180.110.21421/422212CD4_m20cg07376232AMICA1NM_153206001605930.050.030.520.360.210.20423/424213CD4_m21cg18059933TP53INP1NM_033285001649380.230.160.500.430.100.100.31425/426214MOC_nm1cg02780988KRTHA6NM_003771001263370.710.080.690.640.540.640.62427/428215MOC_nm2cg18854666SLC11A1NM_000578000182800.610.140.940.940.790.92429/430216MOC_nm3cg18589858SLCO2B1NM_007256001374910.730.150.890.860.580.81431/432217MOC_nm4cg22456522LILRB3NM_006864002045770.840.170.800.830.680.80433/434218MOC_nm5cg27443224CCL21NM_002989001370770.670.170.630.600.520.520.64435/436219MOC_nm6cg22954818APOBEC3ANM_145699001283830.550.200.650.610.500.650.64437/438220MOC_nm7cg05445326TM4SF19NM_138461001451070.910.210.930.930.580.64439/440221MOC_nm8cg10045881CHI3L2NM_001025197000648860.610.210.660.730.620.690.77441/442222MOC_nm9cg11051139LOC144501NM_182507001677670.580.210.760.770.740.700.71443/444223MOC_nm11cg01193293SIGLEC7NM_014385001689950.650.290.660.660.600.50445/446224MOC_nm12cg04387658CD86NM_006889001140130.550.330.760.720.580.570.80447/448225MOC_nm13cg22319147CDH5NM_001795001797760.560.340.950.950.720.90449/450226MOC_nm14cg13253729RgrNM_153615001594960.850.410.940.930.530.90451/452227MOC_nm15cg00412772C19orf33NM_033520001676440.570.420.740.720.520.62453/454228MOC_nm16cg07986773NUP50NM_153645000930000.850.420.900.890.770.83455/456229MOC_nm17cg06407137CD300LBNM_174892001787890.780.420.840.790.800.740.85457/458230MOC_nm18cg12564453CETPNM_000078000872370.610.440.950.940.650.66459/460231MOC_nm19cg02497428IGSF6NM_005849001407490.920.480.950.950.770.94461/462232MOC_nm20cg16501235C1orf54NM_024579001182920.830.480.860.820.750.830.81463/464233MOC_meth1cg05044994FLJ42393NM_207488002131320.470.740.160.240.320.17465/466234MOC_meth2cg23213217DEGS1NM_144780001437530.040.730.040.030.240.38467/468235MOC_meth3cg24921858BCL2L14NM_030766001213800.480.640.440.420.220.46469/470236MOC_mcth4cg07747299C21orf56NM_032261001602840.470.630.390.350.340.370.27471/472237MOC_meth5cg20839025PRSS7NM_002772001546460.430.630.430.380.400.310.32473/474238MOC_meth6cg15551881TRAF1NM_005658000565580.080.620.160.060.480.21475/476239MOC_meth7cg17233935DSCR10NM_148676002333160.460.620.390.320.320.380.31477/478240MOC_meth8cg07376029GCNM_000583001453210.470.610.250.370.310.390.31479/480241MOC_meth9cg14893161FLJ32569NM_152491001628770.360.590.350.220.400.300.25481/482242MOC_meth10cg24884084SPRR1BNM_003125001694690.450.570.390.430.240.41483/484243MOC_meth11cg12022621LAX1NM_017773001221880.480.560.020.030.340.10485/486244MOC_meth12cg16399745CNAP1NM_014865000102920.450.540.270.260.290.130.10487/488245MOC_meth13cg10117369LAX1NM_017773001221880.460.530.020.050.430.15489/490246MOC_meth14cg24988345SCHIP1NM_014575002505880.440.510.220.270.260.140.25491/492247MOC_meth15cg03427831MTHFRNM_005957001770000.360.500.270.250.240.130.08493/494248MOC_meth16cg05546044MAPK1NM_002745001000300.300.500.150.180.160.12495/496249GRC_nm1cg22381196DHODHNM_001361001029670.050.720.890.840.780.780.87497/498250GRC_nm2cg06270401DYRK4NM_003845000102190.060.800.840.820.790.810.75499/500251GRC_nm3cg22266967S100PNM_005980001639930.080.560.710.690.580.660.60501/502252GRC_nm4cg21283680SH3BP5NM_004844001313700.120.600.770.720.610.640.74503/504253GRC_nm5cg20720686PORNM_000941001279480.150.520.800.770.760.740.74505/506254GRC_nm6cg12949760KCNQ1NT_009237000539180.170.580.760.770.600.770.66507/508255GRC_nm7cg01718139UNQ3033NM_198481001890680.180.720.780.720.780.780.74509/510256GRC_nm8cg05681757FGD4NM_139241001391320.190.710.660.690.670.740.57511/512257GRC_nm9cg00145118GNPDA1NM_005471001135520.190.510.600.670.580.620.74513/514258GRC_nm10cg10758292DEFA1NM_004084002060470.200.900.760.750.780.830.75515/516259nGRC_nm11cg22438810LCN2NM_005564001483460.200.810.740.720.650.600.64517/518260GRC_nm12cg02593766EPN3NM_017957000492830.200.670.810.710.760.830.73519/520261GRC_nm13cg06625767F12NM_000505001311870.210.650.870.870.860.860.89521/522262GRC_nm14cg18934187STARD6NM_139171001744480.220.740.770.620.620.550.72523/524263GRC_nm15cg26306976ITGB1BP1NM_022334001191850.220.920.900.870.810.870.72525/526264GRC_nm16cg09948350FLJ25084NM_152792002446170.230.670.720.640.590.660.71527/528265GRC_nm17cg13265003SLC37A1NM_018964001601900.240.750.810.810.690.790.74529/530266GRC_nm18cg25600606HIPK3NM_005734001104220.250.860.910.840.770.890.88531/532267GRC_nm19cg12788313MST1NM_020998001735310.260.640.920.930.820.89533/534268GRC_nm20cg17051440CLDN2NM_020384001653760.270.610.790.770.680.570.71535/536269GRC_nm21cg24422489FCGR2ANM_021642001432260.270.680.800.730.680.700.81537/538270GRC_nm22cg15361231GLRX2NM_016066000235720.270.640.830.750.620.670.77539/540271GRC_nm23cg10591659NYXNM_022567001889370.280.880.890.820.760.590.84541/542272GRC_nm24cg20098659CLEC9ANM_207345001979920.290.860.890.890.530.86543/544273GRC_nm25cg16504798MYO1FNM_012335001423470.300.560.880.790.770.69545/546274GRC_nm26cg15379858ChGnNM_018371001474080.310.920.930.930.930.940.87547/548275GRC_nm27cg07423149CHI3L1NM_001276001330480.320.510.790.840.780.720.76549/550276GRC_nm28cg17823175AZU1NM_001700001722320.350.520.850.850.850.870.83551/552277GRC_nm29cg21685427SGK2NM_016276001010490.360.600.900.900.910.910.87553/554278GRC_nm30cg11849692LDB1NM_003893001987280.360.710.600.790.570.89555/556279GRC_nm31cg22286764C3orf35NM_178339001985900370.810.940.950.670.95557/558280GRC_nm32cg18530324KIAA0427NM_014772001340300.380.520.860.870.780.80559/560281GRC_nm33cg22630748INHBENM_031479001392690.390.740.940.930.930.930.90561/562282GRC_nm34cg03311899GPR109ANM_177551001827820.430.540.950.930.920.910.95563/564283GRC_nm35cg00840516HYAL2NM_003773002619210.430.750.910.880.890.84565/566284GRC_nm36cg02039171CEBPENM_001805000920670.430.800.940.950.950.940.92567/568285GRC_nm37cg05826823CIZ1NM_012127001483370.460.830.940.920.810.85569/570286GRC_m1cg02212836LY86NM_004271001127990.900.140.080.140.070.42571/572287GRC_m2cg08136806KRT6ENM_173086001704650.650.480.320.390.410.390.27573/574288GRC_m3cg18959422MYBPHNM_004997001330550.640.410.410.480.370.420.34575/576289GRC_m4cg05106502SCAP1NM_003726001412930.610.490.030.030.100.04577/578290GRC_m5cg10896774C7orf34NM_178829001651310.550.450.180.220.230.380.12579/580291GRC_m6cg00323915GIMAP4NM_018326001335740.550.420.170.280.430.200.19581/582292GRC_m7cg12605747RPL4NM_000968001744440.540.410.360.330.310.260.34583/584293GRC_m8cg15625636GPR65NM_003608001400300.540.320.120.200.290.310.25585/586294GRC_m9cg12810837CLEC2DNM_001004419000694930.520.450.110.150.180.140.16587/588295GRC_m10cg26839325BMP15NM_005448001303850.520.450.240.240.240.270.18589/590296eGRC_nm1NAPRG200186652NANANANANANANA591/592297OTL_nm1cg07728874CD3DNM_000732.3001672860.870.910.140.110.910.870.21593/594298OTL_nm2cg24841244CD3DNM_000732.3001672860.830.840.100.070.860.800.16595/596299OTL_nm3cg15880738CD3GNM_000073.1001606540.870.880.070.060.880.840.12597/598300OTL_nm4cg07545925CD3GNM_000073.1001606540.780.760.220.320.660.660.23599/600301OTL_nm05cg24612198CD3ENM_000733.2001988510.740.790.100.140.630.600.11601/602302OTL_nm06cg04759756SLA2NM_032214.2001010820.910.910.210.120.910.730.20603/604303OTL_nm07cg08539991ZBTB32NM_014383.1000115900.840.890.180.190.580.750.17605/606304OTL_nm08cg18350391IL32NM_001012631.1000085170.820.870.150.130.820.680.18607/608305OTL_nm09cg19812619ITGB7NM_000889.1001396260.900.900.290.250.630.710.28609/610306OTL_nm10cg20366831APBA3NM_004886.3000111320.680.810.200.210.740.650.24611/612307OTL_nm11cg22670733CHRNA3NM_000743.2000806440.780.820.220.220.820.800.45613/614308OTL_nm12cg16173109FLJ38379XR_001026.1002040980.870.860.110.280.720.720.53615/616309OTL_nm13cg00620024PPP6CNM_002721.3001194140.860.850.180.280.690.740.44617/618310OTL_nm14cg15503752ST6GALNANM_018414.2000705260.750.740.130.250.590.660.17619/620C1311OTL_nm15cg15055101SH2D3ANM_005490.1001257310.770.820.190.340.720.700.48621/622312OTL_nm16cg18149207RORCNM_005060.3001433650.850.870.520.240.750.740.58 623/624313OTL_nm17cg16854606DAND5NM_152654.2001792840.660.770.340.310.790.650.27625/626314OTL_m1cg24091474TYROBPNM_003332.2000116000.120.080.840.840.270.100.60627/628315OTL_m2cg25957124DNAH3NM_017539.1001584860.050.040.820.820.050.310.86629/630316OTL_m3cg01526089P2RX1NM_002558.2001084050.030.040.860.840.520.320.85631/632317OTL_m4cg12971694CD72NM_001782.1001371010.110.080.800.770.090.210.67633/634318OTL_m5cg19906550SLC22A18NM_183233.1001106280.030.040.720.780.320.240.63635/636319OTL_m6cg17468997NCF1NM_000265.1001585170.120.100.790.820.060.380.81637/638320OTL_m7cg19399532FLJ35530NM_207467.1002044820.070.060.700.800.060.390.79639/640321OTL_m8cg09208010MMP14NM_004995.2001572270.090.080.800.800.360.280.82641/642322OTL_m9cg15512851FGD2NM_173558.2001461920.120.080.760.730.080.200.64643/644323OTL_m10cg20191453AMTNM_000481.2001450200.160.170.870.850.510.250.89645/646324OTL_m11cg24453664CD59NM_203331.1000850630.070.100.790.790.370.290.82647/648325OTL_m12cg10257049C5orf4NM_032385.1001702710.070.070.750.750.280.210.74649/650326OTL_m13cg16003913MPGNM_001015052.1001031520.050.150.820.810.410.320.82651/652327OTL_m14cg14088811SPI1NM_003120.1000663360.100.070.770.740.080.410.79653/654328OTL_m15cg15146752EPHA2NM_004431.2001426270.260.270.900.860.410.350.87655/656329OTL_m16cg02082571CLEC4ANM_016184.2001117290.230.140.850.870.440.470.83657/658330OTL_m17cg16989646SLC25A15NM_014252.1001027430.040.070.690.590.040.110.54659/660331OTL_m18cg03574571CD22NM_001771.1000121240.120.090.850.750.210.490.75661/662332OTL_m19cg13703437FYBNM_199335.2000820740.120.130.860.810.360.450.84663/664333OTL_m20cg21237418RAB34NM_031934.3001091130.040.040.690.610.090.180.75665/666334OTL_m21cg01129847C19orf35NM_198532.1001883050.080.120.690.620.180.060.53667/668335OTL_m22cg16139316S100A9NM_002965.2001632200.060.070.840.730.490.370.85669/670336OTL_m23cg00666746SYDE1NM_033025.4001051370.080.070.710.580.180.110.58671/672337OTL_m24cg20050826K6IRS2NM_080747.1001704860.140.180.770.690.190.270.59673/674338OTL_m25cg12876594NPR2NM_000907.2001396260.230.190.790.760.310.260.77675/676339OTL_m26cg17105014GYPCNM_002101.3001367320.130.140.760.700.350.260.68677/678340OTL_m27cg03886110PECAM1NM_000442.2002613710.050.070.770.500.350.090.47679/680341OTL_m28cg14324675LST1NM_205838.1002044820.050.040.630.710.240.360.65681/682342OTL_m29cg08519905CD9NM_001769.2000102780.100.120.710.610.110.350.68683/684
TABLE 4ANatural Killer Cells - MarkersNon-Baso-Eosino-Neutro-Classi-classi-philphilphilcalcalNKMarker-Granulo-Granulo-Granulo-Mono-Mono-classi-IDTargetIDSYMBOLAccessioncytescytescytescytescytescalNK_nm33cg24433034——0.970.970.970.970.950.09NK_nm34cg27274718ANKRD28NM_0151990.920.890.910.910.870.08NK_nm35cg07802362DNM3NM_0155690.900.910.920.920.900.12NK_nm36cg13292607CTBP2NM_0010839140.950.910.920.930.920.16NK_nm37cg04064701RHOBTB1NM_0148360.910.900.930.930.910.16NK_nm9cg03368758LDB2NM_0012900.900.850.880.880.860.16NK_nm39cgl7893934LARP4BNM_0151550.970.960.960.960.960.22NK_nm40cg16360310CXXC5NM_0164630.870.820.850.870.840.15NK_nm4lcg23549472RNF165NM_1524700.850.860.870.880.880.18NK_nm42cg13620110EIF3GNM_0037550.940.910.920.920.930.27NK_nm43cg23060465EIF2C2NM_0121540.970.970.970.970.960.33NK_nm44cg21275838MYO1ENM_0049980.880.900.890.890.890.27NK_nm45cg15259233FAM120BNM_0324480.880.860.880.890.870.30NK_nm46cg11790417——0.880.900.880.890.890.31NK_nm47cg06068163EIF3BNM_0010372830.890.870.900.900.870.33NK_nm48cg14259466ADAM8NM_0011090.890.710.960.960.930.17NK_nm49cg10592926ZDHHC14NM_1537460.900.940.950.950.920.22NK_nm50cg05253716SLC15A4NM_1456480.910.910.920.930.890.22NK_nm51cgl7162797RASA3NM_0073680.920.910.920.940.920.31NK_nm52cg00462849——0.940.940.950.940.920.35NK_nm53cg10055950CIGALT1NM_0201560.910.920.920.910.890.13NK_nm54cgl9915997COLQNM_0805380.860.870.880.880.870.07NK_nm55cg06706159MAST3NM_0150160.970.970.980.970.940.19NK_nm56cg23015664MAD1L1NM_0035500.920.940.960.940.940.04NK_nm57cg21828319RFC2NM_1814710.690.920.920.910.900.08NK_nm58cg05421487AKAP10NM_0072020.750.850.900.900.890.21NK_nm59cg24467387SBNO2NM_0149630.840.910.930.920.880.23NKT_nm21cg05585475——0.890.860.890.900.900.83NKT_nm22cg20063728PDGFANM_0026070.910.890.890.910.900.85NKT_nm23cg00879541C14orf166NM_0160390.910.900.890.900.840.87NKT_nm24cg26215982——0.920.910.900.900.910.83NKT_nm25cg08455089TBC1D22BNM_0177720.850.840.900.880.840.86NKT_nm26cg09046550——0.870.890.870.890.880.83NKT_nm27cg27316453LDHAL6ANM_0011440710.890.900.900.880.860.80NKT_nm28cg03069731ST7NM_0184120.900.860.860.870.870.84NKT_nm29cg23642827——0.890.920.900.910.900.82NKT_nm30cg12219570ZAKNM_0166530.880.870.910.930.910.83NKT_nm3lcg16548262——0.890.790.800.840.840.79NKT_nm32cg05844859NCRNA00119NR_0028110.870.900.880.870.870.82NKT_nm33cg15740507TBC1D23NM_0183090.880.790.860.820.760.77NKT_nm34cg07406728——0.840.850.890.870.830.83NKT_nm35cg13994599SAMD4ANM_0011615770.820.800.810.810.820.81NKT_nm36cg03345391GCKNM_0001620.840.860.870.820.830.82NKT_nm37cg07891862PTK2NM_1538310.910.910.900.910.870.84NKT_nm38cg25503323AOAHNM_0016370.870.880.840.880.890.83NKT_nm39cg24037746C3orf30NM_1525390.900.900.900.880.870.73NKT_nm40cg13382516SGMS1NM_1471560.880.860.890.890.890.79NKT_nm41cg25918166——0.850.840.850.840.830.80NKT_nm42cg08250738——0.900.920.920.930.930.86NKT_nm43cg19083007RCAN2NM_0058220.860.850.860.870.850.84NKT_nm44cg06228763ELFN1NM_0011286360.800.760.770.800.780.75NKT_nm45cg19243780UBE2E2NM_1526530.820.820.850.890.840.83NKT_nm46cgl1571124CLIP1NM_0029560.890.880.900.890.880.72NKT_nm47cg17569413——0.890.880.890.880.890.90NKT_nm48cg14089425KCNQ1NM_0002180.860.870.890.900.860.80NKT_nm49cg26894807GPR89ANM_0010976130.850.890.890.890.900.85NKT_nm50cg02791542OSBPL10NM_0177840.860.860.850.860.840.77NKT_nm5lcg24585690IL9NM_0005900.860.850.870.870.870.85NKT_nm52cg18904552TNKS2NM_0252350.870.820.890.900.890.88NKT_nm53cg18077068——0.880.870.890.850.860.84NKT_nm54cg03905757KCNQ1NM_0002180.830.860.860.850.840.77NKT_nm55cg12630243——0.910.860.880.910.910.84NKT_nm56cg12399350——0.830.800.810.860.860.73NKT_nm57cg00829600——0.860.830.790.870.880.79NKT_nm58cg24722886PLEKHA7NM_1750580.860.810.840.830.850.75NKT_nm59cg16565562——0.870.830.840.870.870.81NKT_nm60cgl3362028——0.790.780.760.760.770.74CD8+CD4+CD4+Cyto-CD4+ThThtoxicNKMarker-B-ThCD4+CD4+CentralEffect.T-T-DiscoveryIDCellsnaiveTh1Th2Mem.Mem.CellsCellsFragmentNK_nm330.970.970.970.970.960.950.930.80CGCTCCCCAAGTGCTGACCACGCGCGCCCCCACGGCTCCCCGACAGCTCC(SEQ ID NO: 696) NK_nm340.900.920.900.910.910.920.890.87AGTAGGTAAAAACACTGATGCACTCTGCTTACCATGTAAGCCTCTTAACG(SEQ ID NO: 697) NK_nm350.900.910.860.870.900.900.830.83CGGCTCCAAATCAAAAGCTGTGGAAGGAGGTAATTAGCAGGGACTCTAGA(SEQ ID NO: 698) NK_nm360.930.940.890.890.910.910.870.85TTTTGTTGGTTCCTCACGTGGGCAGAAGAGTGAATGCTCAGTCCCCATCG(SEQ ID NO: 699) NK_nm370.920.910.910.920.910.910.890.84AGCTGATACTGCGTGAGTGTGGTGTTGCACGCCCTGGCACAGATCAAGCG(SEQ ID NO: 700) NK_nm90.880.890.930.910.930.930.910.90CCCTTCACAACCTGATTGCTAAGCTTGTTAGCATAGAGGTGGTCTAACCG(SEQ ID NO: 701) NK_nm390.970.970.950.960.960.960.930.87AAAACCGTACGTCTGGGAGGGGTCGCAGAGCGCTGTGTTAACCACAAACG(SEQ ID NO: 702) NK_nm400.860.850.860.870.860.860.870.84CCATTACCACTGGCTTTGTTACAATCTATTACAACAATAGCAGTTGGCCG(SEQ ID NO: 703) NK_nm4l0.920.840.860.850.870.860.830.84CGGAAGGGCAACAGAACAAAAGCAGCGTACAATGAGCAGATGGCCCGGGC(SEQ ID NO: 704) NK_nm420.940.940.910.900.950.940.930.87GGGGATAATTACGAGGTGCCGGGAGGTGCCCACCCACCAGCCTGGCGTCG(SEQ ID NO: 705) NK_nm430.970.970.970.970.970.970.940.93CAGAGGGCTCTGAGCGGGCTGTGTGCCGGGCGAGAACACTGCCTGGGCCG(SEQ ID NO: 706) NK_nm440.860.880.900.900.900.890.900.87CGCAGCTTATTTGTCACTGAGAAAGTTCAAGTTAGTGCTCTAATTCCACC(SEQ ID NO: 707) NK_nm450.890.890.870.860.870.890.900.85CGGGGCAGCTGCCTGCACTGAGCTCTGAGGCCTTTGAAGTGGACCAGAGA(SEQ ID NO: 708) NK_nm460.880.880.850.870.890.870.890.85TTAAGGGCCAACCCTGACCACAGCTGAGCCGTGTGAAGAGGCTGACAGCG(SEQ ID NO: 709) NK_nm470.890.900.870.860.870.890.890.88CGGCTACAAGCTTGACAAGCAGCACACATTCCGGGTCAACCTCTTTACGG(SEQ ID NO: 710) NK_nm480.930.870.960.960.960.960.960.92CGGCGTCTCCAGGCCTGCGGCCAAGCGTGCTTGCCCTTGGTGACCACATT(SEQ ID NO: 711) NK_nm490.930.860.910.920.940.930.910.92GGCGCTCTGCCTGCAGCTATCTCCGTGTCAATGGCATCCTTTGATAGTCG(SEQ ID NO: 712) NK_nm500.910.920.910.910.910.920.910.79CGCCAGAGTAATGGGTAAGCACTTAGTTCTCATCTTGGGCTGTTTGAAAG(SEQ ID NO: 713) NK_nm510.910.920.910.930.920.920.930.91CGCTAAACGGTGCCACAGTTTTACTCTCTTGGAACTGTCCCACATGGGTT(SEQ ID NO: 714) NK_nm520.940.950.930.920.940.940.950.92CGAGGCATCGGCCCGTTTTGTGTCTGGTAAGGGCCAGAGTCCTGGTTCAT(SEQ ID NO: 715) NK_nm530.900.920.920.920.930.890.910.81CGCTCACTGCTTACTTAAATGGACAGTTTTAAGTTTCAGTTTTAAGCTCA(SEQ ID NO: 716) NK_nm540.870.860.810.820.850.830.820.73CGTGCAGGCATTCTCACTCACACTGGGCAGCCCGCTGTCGGGTCTCTCTA(SEQ ID NO: 717) NK_nm550.980.980.980.980.980.980.880.70CGAGCTCGGCCTCTGGCCCACGAGTGCGCCGCCCCGCCTCCCCATCCAGC(SEQ ID NO: 718) NK_nm560.950.930.950.950.940.960.920.80CGCGGACCCCGCTTCTGTCACCCCTAACCTCACTGTTGGGTCCGGGACCT(SEQ ID NO: 719) NK_nm570.740.670.910.920.920.920.900.84CGGGGCACAGACGTCCCAGAAGCAAACATGCAAGTCACGGGAGTTTATTT(SEQ ID NO: 720) NK_nm580.900.760.860.880.890.900.850.83TCTATATCTGATCCATCAGCAAATCTGTTAGGTCTACCTCACACATATCG(SEQ ID NO: 721) NK_nm590.910.830.880.900.930.900.880.82GTGGGTCTCACTCAGCTGGGCGCTGGGGCCCTGGTGGAGAATGGCTGTCG(SEQ ID NO: 722) NKT_nm210.810.900.810.830.860.860.670.27CGGTAGACAAATGATAGACATTTGTTGAATCAAGCTGTGAGTTGGAGATC(SEQ ID NO: 723) NKT_nm220.890.900.690.850.820.790.630.13GTCTTTGCCTGACACCTTCTGTGAGGTTTGCGGGCTTCATTTTAAATCCG(SEQ ID NO: 724) NKT_nm230.840.870.720.800.810.770.700.17GGGGTTATATATTTTTGACCAAATTCACCATTACTCATTTGGCATTTTCG(SEQ ID NO: 725) NKT_nm240.810.890.590.700.740.670.590.15GCGTACACACCCTGATAAGGTGTCAAGAACCTCCGTTTGAGTACCCCTCG(SEQ ID NO: 726) NKT_nm250.810.840.510.620.610.480.600.15CCTGCTGTAGATGTGTCACAGCTAAAITCTTGAATGGATTTTTATCATCG(SEQ ID NO: 727) NKT_nm260.870.880.510.700.630.600.690.22GAACCAAGCACTGCTTCCTGGGAGAGTGATGTCAGCATGACTCAAAGGCG(SEQ ID NO: 728) NKT_nm270.820.910.550.650.680.600.690.23CGCAAACCCACCCTCTATCCGGGTGAGCACCATCTAGTCAGCTGCCAGCA(SEQ ID NO: 729) NKT_nm280.820.870.560.700.670.610.680.24CGTGGGATCTCTGTTCATTTTGGTATATTACTTTGCTTTCTGGGCTGAGC(SEQ ID NO: 730) NKT_nm290.800.910.600.790.770.740.590.26CGCATACTTTCAGGGAGAGGCACTATTCTTGGCTTTAAGTTCATGAGTAA(SEQ ID NO: 731) NKT_nm300.820.880.570.610.670.600.680.25CGGGGGGAGAATTAAGCCAAAGAAGTATATTTATGAATCAGCAAATGTGG(SEQ ID NO: 732) NKT_nm3l0.820.900.610.790.710.710.680.24CGGCTTGAACCCTCAGCTTCTACAGTTGTGTCACCCATGTGTCTGTTTCT(SEQ ID NO: 733) NKT_nm320.800.860.550.540.660.590.680.24GGCCGAGGTGAAACCATTGGTTTTTAACCTTGACTACTGATTAAAATCCG(SEQ ID NO: 734) NKT_nm330.800.880.590.740.680.610.660.24ATCAGCACCAAAGCTTTGTCTGAACTTATTTTGCTACTATTGTTAGGACG(SEQ ID NO: 735) NKT_nm340.860.850.570.670.680.640.680.27CGACTGTGGGGAATGAATAAGATTACAATAAAACCTGAGGAATTTAATGC(SEQ ID NO: 736) NKT_nm350.800.870.540.570.660.620.670.26CGAGTGAGTCCAAACTCCTTAGAAAGTTGGTTGCTAAGGACTTGGAAAAG(SEQ ID NO: 737) NKT_nm360.800.850.570.580.700.610.690.28CCCTTCCCCAAGTTCCATACAGACCCCTGGATTGTATGAAATGCAAATCG(SEQ ID NO: 738) NKT_nm370.810.880.580.670.720.620.660.14CGGAGAGCAAACAGGGCTAACACAGAAAGCCCTTGTAAAAAACAGAACGA(SEQ ID NO: 739) NKT_nm380.870.880.500.610.670.600.610.15CGAGGAAGGTATGGTAGAAATGCATCCATTACCAAGAAGAAAAGTAATCT(SEQ ID NO: 740) NKT_nm390.830.890.600.760.750.710.660.20CACATCACTATATGGAACACGACTATACTTTCAAAAGATGACCAATCTCG(SEQ ID NO: 741) NKT_nm400.750.880.670.740.720.690.610.20CGTGCCCAGCTTTTCTATGGGAAAAATTGTTCTTCAGACAGAGCATGAAT(SEQ ID NO: 742) NKT_nm410.780.840.480.600.680.590.580.17CGTCATTATCTGGCAATAGTTGTTGGATGTGTTTGCTGCCATGCCACGAG(SEQ ID NO: 743) NKT_nm420.780.890.620.700.710.680.630.26CGTAGGTTTCCAAGAAAGATAGGGTGACAAAATTGCCTGTCACTCCGATT(SEQ ID NO: 744) NKT_nm430.770.870.490.590.640.600.650.21CGGATTTCTATTCAGCCCATGCCCGGGATGCATTAGGATGCCCAGAACAT(SEQ ID NO: 745) NKT_nm440.740.810.490.510.510.450.520.14GGGAGTGGCCCAGCCCGGTTTGCTCAGTGACCAGGATGTTTCCACAGTCG(SEQ ID NO: 746) NKT_nm450.870.840.460.500.630.540.690.21GTGGTCTGGTTACATCAGCAAACATGTTCTACAATCAAGGTAAAAACTCG(SEQ ID NO: 747) NKT_nm460.830.870.510.620.600.560.660.23CGAGTACTAAAAGGTCAAATGTGTCAAGTCTAGAACTAGTACTCTTTTTT(SEQ ID NO: 748) NKT_nm470.830.910.530.700.630.590.700.26CGCACCATCACACCGTCAGCAACTTGTGGGACCAACTCCCTGCACATCTG(SEQ ID NO: 749) NKT_nm480.760.850.570.700.750.700.700.25AGTACATCTGTTGACAACATGGTTTACTGAATATGTTGAGCCCATTTTCG(SEQ ID NO: 750) NKT_nm490.800.870.570.470.640.630.610.23TCTATCTTCATTTAACTTCCAGTCCTTTGCCCTACAGATAATTCGTAGCG(SEQ ID NO: 751) NKT_nm500.820.870.490.530.610.560.610.21CGGCCAAAAGAAAGACATAGAATAGAATGGTGGTTGCTGAGGGTTGGAGA(SEQ ID NO: 752) NKT_nm5l0.780.880.620.590.680.670.670.24CGGACTGGAGCTCGCTTGCAGACACCTTCAAATCGAGTGGTATITAAAGC(SEQ ID NO: 753) NKT_nm520.890.880.500.620.580.530.740.27ACAAACAAAAAGCTATCTGAAAATGCTGCCATGCTAACAPATGAACCACG(SEQ ID NO: 754) NKT_nm530.770.870.510.560.630.520.690.26CGAATGGAAATTCAAAGGGAGAACATCTAATGTTCAAGTTGATGTCTATA(SEQ ID NO: 755) NKT_nm540.790.840.580.660.730.680.620.26CGTCCCCTCTAATACTATAGCTGAGAGCTTTTAATATGAATGGGTGTTAA(SEQ ID NO: 756) NKT_nm550.770.890.510.570.660.610.690.28CGACTGGTGTTGATTCTCAGTCAATTTAAAGGATGAAAAGGGCTGTAAAA(SEQ ID NO: 757) NKT_nm560.790.820.540.650.620.580.640.25CCCAGTTCTTCAGAGTTGTCAGGGTCACTGCTCTGGGACCCACGGACTCG(SEQ ID NO: 758) NKT_nm570.840.840.490.550.600.550.610.26CGAAGGAGGGAGTGCATGAATTCATGTAAGGATGGAGATCCACATCCCAG(SEQ ID NO: 759) NKT_nm580.810.820.550.570.660.610.590.26CGAGTGTGGAGCTATGATTGGAACCTAGTTCAGGCTCCAAAGCCACACTC(SEQ ID NO: 760) NKT_nm590.760.850.480.520.640.590.670.28CGGATTTTTGAGACAGTTTGGGAATAGTTTATCCTGTTATTATCTTCAGG(SEQ ID NO: 761) NKT_nm600.730.730.470.510.550.440.610.24CGTTAGGATTGCTAAAGAGCATTTTCTAAATATTTGAGTGTAAACCACTG(SEQ ID NO: 762)
TABLE 4BB-Cell MarkersNon-Baso-Eosino-Neutro-Clas-clas-philphilphilsicalsicalNKMarker-Granu-Granu-Granu-Mono-Mono-clas-IDTargetIDSYMBOLAccessionlocyteslocyteslocytescytescytessicalB_nm45cg22907103CYBSC3NM_1536110.880.870.860.840.830.86B_nm46cg15532942NFATC1NM_0061620.870.910.880.910.890.89B_nm47cg27106643NFATC1NM_0061620.890.920.930.900.870.90B_nm48cg07841371TTLL10NM_0011300450.920.940.940.950.920.95B_nm49cg13738327LRP5NM_0023350.980.980.980.980.970.97B_nm50cg26552743——0.870.840.860.890.850.89B_nm51cg05205074——0.920.920.930.920.880.91B_nm52cg07721872LOC100129637NR_0244880.940.950.930.960.950.93B_nm53cg11661493UBE2ONM_0220660.900.880.890.900.870.91B_nm54cg02212339TRPV1NM_0807040.980.970.970.970.960.97B_nm55cg27564966CD19NM_0017700.910.890.910.910.890.84B_nm56cg25469923——0.850.860.870.860.830.82B_nm57cg22498365TBCDNM_0059930.860.910.920.900.860.91B_nm58cg17232476SORL1NM_0031050.890.900.890.860.830.89B_nm59cg18664915C7orf50NM_0011343950.880.900.880.890.870.88B_nm60cg20602300C15orf57NM_0528490.910.900.920.910.900.91B_nm61cg18250453TERF1NM_0032180.890.850.900.910.900.82B_nm62cg06889975——0.900.840.850.870.890.90B_nm63cg11699517BAHCC1NM_0010805190.990.970.970.970.970.99B_nm64cg15035590LRIG1NM_0155410.910.910.900.920.890.88B_nm65cg15242630MICAL3NM_0011227310.880.880.870.870.850.88B_nm66cg13823257——0.880.880.890.880.860.89B_nm67cg13915752CDK19NM_0150760.880.850.900.900.900.91B_nm68cg04838847GOLSYNNM_0010997430.980.980.980.970.980.98B_nm69cg22281206INPP5JNM_0010028370.880.890.900.880.850.89B_nm70cg19260718——0.870.900.890.900.860.89B_nm71cg19766988EIF3GNM_0037550.890.900.890.900.850.89B_nm72cg20452738ITPKBNM_0022210.900.890.910.880.900.90B_nm73cg26692003IQSEC1NM_0011343820.950.960.970.950.910.96B_nm74cg00762029IRF2NM_0021990.920.910.920.920.900.93B_nm75cg17622855ZDHHC14NM_1537460.870.880.890.890.890.87B_nm76cg04947949WDFY4NM_0209450.880.910.920.910.890.88B_nm77cg25131632——0.960.970.970.970.960.96B_nm78cg14482811LCN8NM_1784690.930.920.960.950.950.70B_nm79cg12177944PLXND1NM_0151030.960.960.940.860.680.97B_nm80cg21248060C7orf50NM_0011343950.960.960.970.970.950.95B_nm81cg04828493CARS2NM_0245370.950.960.950.860.730.85B_nm82cg01024458RERENM_0121020.920.920.930.920.930.91B_nm83cg25683989HVCN1NM_0010401070.920.770.920.920.910.89B_nm84cg22212560FRMD8NM_0319040.890.860.900.720.620.93B_nm85cg15348679——0.770.830.880.870.860.95B_nm86cg16210395CGNL1NM_0328660.920.920.930.940.930.90B_nm87cg08162476IQSEC1NM_0011343820.910.920.910.780.740.88B_nm15cg07597976CD19NM_0017700.860.820.820.820.780.77B_nm89cg07768103RNF44NM_0149010.980.980.980.980.980.96B_nm90cg13356455ATP10ANM_0244900.910.890.900.900.900.88B_nm91cg17995557LHPPNM_0221260.870.900.870.890.870.62B_nm92cg17679619——0.900.850.890.890.880.88B_nm93cg27304328CD84NM_0038740.890.610.840.840.830.88B_nm94cg26438284CD81NM_0043560.890.840.870.890.880.86CD4+ThCD4+Cen-CD4+ ThCD8+NKMarker-B-ThCD4+CD4+tralEffect.CytotoxicT-IDCellsnaiveTh1Th2Mem.Mem.T-CellsCellsDiscovery FragmentB_nm450.040.870.850.860.880.870.870.86AGTCATTGTGACTGAAGATCAGGCCCACCCAGGCATTGAGGCCTCGGGCG(SEQ ID NO: 763)B_nm460.070.870.860.850.830.840.880.85CGGCCAGGCCCTCATCCACCAGAGTAGACCCCAGCACGAGCAGGCGTCGC(SEQ ID NO: 764)B_nm470.110.900.900.890.890.900.920.91GCTTTCCACGGCTGTGCGCCTCGGGGCTGGAGCGGCCCCAAGTGAAGACG(SEQ ID NO: 765)B_nm480.100.940.940.930.940.940.930.92CGCGGCCCAGGGTTCCGCCTGGCTGGCACCACCCCTGGAAGGGCAGCCCC(SEQ ID NO: 766)B_nm490.030.970.930.960.970.960.950.88CAACGTGAAGAAAACGTGAAATTCTGTCGCTTGTTGCAGCTGACAGCACG(SEQ ID NO: 767)B_nm500.040.860.860.890.870.860.890.87AAACAGGATCTCTGCAGATGGAGCTCAGTGTTATGTGTTTTGGATGCTCG(SEQ ID NO: 768)B_nm510.040.920.860.840.870.870.920.88CGCCCTGGCCTGAAGGGAAGAGTCTACAAGGTTTATAACCCAGAACCGCA(SEQ ID NO: 769)B_nm520.030.930.940.940.910.930.940.93CGTCCGCCTCGTCCACTCCTGGCATTTGGGATAAACATCCTGTCTCAGAC(SEQ ID NO: 770)B_nm530.040.890.890.900.910.890.890.89CCCTGAAATCGACCCTAACAATAATAGAGGTTTGGATTTGCATGAACACG(SEQ ID NO: 771)B_nm540.050.970.950.950.970.960.960.95CGCCATCGAGAGACGCAACATGGCCCTGGTGACCCTCCTGGTGGAGAACG(SEQ ID NO: 772)B_nm550.060.900.910.900.890.910.920.90TTGTGAGTCTGGAGGGTTCCTGGAGAATGGGGCCTGAGGCGTGACCACCG(SEQ ID NO: 773)B_nm560.060.890.850.870.840.850.870.84CAGGCTACTATTCCTGATGGAGACCCCCATTTCCGTGGCGGCCCCTGACG(SEQ ID NO: 774)B_nm570.070.880.890.910.890.910.890.91TCCTGAAAGTCCCTGGCACAGGACACCACTACGGGGCTCAGCTGGGTGCG(SEQ ID NO: 775)B_nm580.070.890.870.880.890.880.880.88CGCAACCAGTATCGCTGCAGCAACGGGAACTGTATCAACAGCATTTGGTG(SEQ ID NO: 776)B_nm590.070.900.860.880.880.870.870.84CGGGCCAGCCAGGCCATGGCATCTGCCTGCTGGGGGCTGTTTTACTGCTG(SEQ ID NO: 777)B_nm600.070.900.890.910.910.920.910.92TCCTTCAGTGGATTTCTCCCTGCTGCTGTCACTGAGCTCCACGCTGCTCG(SEQ ID NO: 778)B_nm610.080.890.880.870.890.890.900.88TTTTTACAAATTGAAAGTTTACCGCAGCCCAGCTTGAGCCAAGTCTAACG(SEQ ID NO: 779)B_nm620.080.890.900.900.910.900.900.89CTTTATCCAGCAAGAAGCCAGCTGTGTGGCAAGCAATGGAGGTAAGAACG(SEQ ID NO: 780)B_nm630.080.980.980.980.990.990.990.98CCCCGTGGGACGTGGGGCAGGCAGCGAGCTTGAGTGTTTGCGCTTCCTCG(SEQ ID NO: 781)B_nm640.090.920.920.880.920.910.910.89CGGAAAGCCCCATTCACAGGATTTGCATTGATTTGCCCTGATCTAGTTTG(SEQ ID NO: 782)B_nm650.090.880.860.870.860.880.880.86CGGGGCAGTTTTGTGGCCTTTTGCTATTGAATCTGCCAGATGTGTCCAAG(SEQ ID NO: 783)B_nm660.090.880.850.870.880.880.890.84AGAGCAAGTCAGGCACACCATACTCTACCTGGAACAGCTGCTAAACTCCG(SEQ ID NO: 784)B_nm670.100.890.900.900.900.900.920.89CCCTGACAAAACAAACTCTGTAAGCTGTGTCAGCCATGCAAGGCACCACG(SEQ ID NO: 785)B_nm680.100.980.980.980.970.980.980.98CGCCTTCCGTATCAAAACCTAAATAGAAGTTGTTGTTACCGTGTGCCAAT(SEQ ID NO: 786)B_nm690.100.890.880.870.870.870.890.85CCCACTCTGTGACGCTCAGAAGATAGCATCCCCTCCTAAGGAACTTGCCG(SEQ ID NO: 787)B_nm700.110.870.880.880.890.870.900.85CGTCATTGCCAACTCCAATGCCTCAATGCACATGGCGGGGCCCAGCCACA(SEQ ID NO: 788)B_nm710.110.890.870.860.880.860.900.90CTCCCTGAGGACCAGTTTTTTCCCCTGGGGAGTCATCATGAATCACTTCG(SEQ ID NO: 789)B_nm720.110.910.880.880.900.900.900.89CGGCTGCCCAACCCTGACTCCAGGCTGGACACTGGAGATGATGCAGACCA(SEQ ID NO: 790)B_nm730.120.970.960.960.960.970.960.96ACTCAGTGACTGACGTTTACGGTCACACGAAGGAATCACTACACCAAGCG(SEQ ID NO: 791)B_nm740.130.920.910.910.920.920.920.91CGCACGGGCTCTGCCGTTCAGAACACAGCCACATCCCGTGATCTCATTTG(SEQ ID NO: 792)B_nm750.130.880.850.860.890.880.890.88CTGAGTTTTCATCAAACACCTGCTGAGCAGCTGGCACGTGCCAGGACACG(SEQ ID NO: 793)B_nm760.130.900.890.900.900.890.880.86CTAGAGACAAGCGATGAGCTGCACTGAGGATCAAGGATCAGGCATTAGCG(SEQ ID NO: 794)B_nm770.030.970.900.910.920.910.920.78CATCTGGGTGGCTGGAAACCCAAGAACGGTGCCTAGCTCGGCTCTGTCCG(SEQ ID NO: 795)B_nm780.040.900.960.940.970.960.970.95GGGCTCGTTCTGGCCTGCGCTGCGAGGGCTGTGGGCACTGATGGGCAACG(SEQ ID NO: 796)B_nm790.050.970.930.920.950.940.950.93CGAGGTCGGTCTCCCACGACTGCCCACCATCTGGCCGGCCACCCTGAAAG(SEQ ID NO: 797)B_nm800.100.970.960.970.970.970.970.96CGTGCCTGCCCCGCCGTGCACACACCTCAGCCCCCGGGAGACGTGCCTGC(SEQ ID NO: 798)B_nm810.050.960.920.950.950.930.930.83CGCCCCCACTCAGTCACACGACACTGCTCTCCTGGCCCACTGCGGCATCC(SEQ ID NO: 799)B_nm820.030.920.760.800.820.820.910.87CGCTAACATTATGCTCTGTGGCAGGTTGCCCTGTCTGCTGTGCTCACCTT(SEQ ID NO: 800)B_nm830.060.910.890.920.900.910.900.89CGCTGGTTGACTGGCAGAGCAACTTCTGGACCCAGCAGAGTTCAGCTTTG(SEQ ID NO: 801)B_nm840.030.900.910.940.930.930.930.92CGTGCTCCAAGAAGTACAAAGAAAAAGTCAAAGCTACAGCCGCTGACGGC(SEQ ID NO: 802)B_nm850.030.820.860.830.850.790.960.94CGATATAAAATGAACGCGCGTTCAAGATTTCCTTCAACTCATTGTTAGCG(SEQ ID NO: 803)B_nm860.060.930.790.830.850.800.850.76CGGTTTACCACACCACCCTTGACTGGGAAATGGGGCTAAGATTTTAATAA(SEQ ID NO: 804)B_nm870.050.920.870.890.890.880.930.86GGCCAGGGGAGCAGTGAGTCACTCAGGGCGGGATGGGTGAGGGGCGTCCG(SEQ ID NO: 805)B_nm150.020.860.840.850.880.870.880.84CGGTCTCTACTCCAAGGGGCTCACATTCTTGTGCAGAAAACAGAAATGAA(SEQ ID NO: 806)B_nm890.150.980.980.980.980.980.800.98CGGAGCAGCTGCCGCGCCTCGAAGTCACTGAAGCAGACCACACACCTGTG(SEQ ID NO: 807)B_nm900.060.900.840.810.840.840.900.81ACCCACAGAGAAGCTGCCATCTAAATAGGGCTGATTTCGAGTTTTGGACG(SEQ ID NO: 808)B_nm910.050.880.880.880.870.890.880.87AGCTCCTAGGTTTGAAAAGTTCTATGTGCGCTTGACCGGGGGGCCTTACG(SEQ ID NO: 809)B_nm920.060.890.860.820.830.840.890.82CGTTAGCAAACACATAGTAGCAGAAACACCTGTCAGAGGACAGTGTCTCA(SEQ ID NO: 810)B_nm930.040.890.860.880.870.890.900.86CGGGATGGAGTTCCCATACCGTAGTTCAGAGGCATAGGGACTTCTGCATT(SEQ ID NO: 811)B_nm940.060.890.850.860.880.880.840.79GACCCCAGGCTGCCATCTTGGCGCTAACTTCTTCCGAGGCAGAGCCAACG(SEQ ID NO: 812)
TABLE 4CCD8 positive T-Cell MarkersNon-Baso-Eosino-Neutro-Clas-Clas-philphilphilsicalsicalNKMarker-Granu-Granu-Granu-Mono-Mono-clas-IDTargetIDSYMBOLAccessionlocyteslocyteslocytescytescytessicalCD8_nm12cg00219921CD8ANM_0011458730.910.900.920.900.890.90CD8_nm13cg25939861CD8ANM_0011458730.870.870.900.560.610.84CD8_nm14cg18857618CD8BNM_1722130.890.880.860.900.870.88CD8_nm15cg03318654CD8ANM_0011458730.710.730.720.730.710.74CD8_nm16cg25535316PHRF1NM_0209010.860.840.840.830.820.86CD8_nm17cg07016730SBF1NM_0029720.880.840.870.770.790.88CD8_nm18cg21648425CD8ANM_0011458730.740.740.750.550.510.67TEMRA_nm1cg04467549——0.920.940.940.650.670.84TEMRA_nm2cg20063728PDGFANM_0026070.890.890.890.850.860.87TEMRA_nm3cg06567722PCID2NM_0011272030.980.980.980.840.850.96TEMRA_nm4cg25002426KIF3CNM_0022540.920.920.890.870.870.91TEMRA_nm5cg21241195C6orf10NM_0067810.920.900.910.880.860.90TEMRA_nm7cg02051545——0.900.910.920.860.850.89TEMRA_nm8cg20960322——0.740.860.840.610.740.78TEMRA_nm9cg06147361SOX5NM_1529890.870.870.880.840.850.89TEMRA_nm10cg05173889TDRD9NM_1530460.910.880.900.860.820.88TEMRA_nm11cg12080492MYBPHNM_0049970.910.900.940.870.880.93TEMRA_nm12cg00922200SEMA3ANM_0060800.840.840.880.870.870.83TEMRA_nm13cg19592003DEFB114NM_0010374990.740.870.840.830.820.76TEMRA_nm14cg14317884EHD1NM_0067950.920.820.850.820.790.91TEMRA_nm15cg00879541C14orf166NM_0160390.890.900.890.870.860.88TEMRA_nm16cg24142603MSCNM_0050980.900.950.950.910.880.93TEMRA_nm17cg05585475——0.890.860.890.830.820.89TEMRA_nm18cg18080819SHANK2NM_0123090.910.880.900.870.860.90TEMRA_nm19cg13486641NINLNM_0251760.920.930.960.940.940.93TEMRA_nm20cg13382516SGMS1NM_1471560.870.860.890.790.780.86TEMRA_nm21cg26215982——0.870.910.900.830.820.90TEMRA_nm22cg03221073HMCN1NM_0319350.900.880.890.870.850.88TEMRA_nm23cg02261543CTR9NM_0146330.930.930.940.880.900.91TEMRA_nm24cg03938110NCRNA00110NR_0270210.880.890.870.870.840.87TEMRA_nm25cg15449516——0.840.860.880.770.790.88TEMRA_nm26cg14365420——0.880.920.910.900.880.89TEMRA_nm27cg03668556——0.900.910.920.870.890.87TEMRA_nm28cg00472528——0.900.890.940.870.810.90TEMRA_nm29cg05633605ANKRD55NM_0246690.820.790.810.810.790.80TEMRA_nm30cg27064867C6orf10NM_0067810.900.910.910.890.860.90TEMRA_nm31cg18449136——0.880.890.890.840.830.87TEMRA_nm32cg13361307AFF3NM_0010251080.810.800.790.780.780.81TEMRA_nm33cg25663823LRRK1NM_0246520.950.950.950.900.900.94TEMRA_nm34cg24722886PLEKHA7NM_1750580.810.810.840.750.720.84TEMRA_nm35cg01252713——0.880.900.870.870.870.88TEMRA_nm36cg09851620——0.900.910.920.880.870.89TEMRA_nm37cg26484813AHNAKNM_0240600.860.890.910.860.850.89TEMRA_nm38cg25370412——0.850.860.840.850.820.83TEMRA_nm39cg12522833GALR1NM_0014800.870.920.920.920.880.87TEMRA_nm40cg26512948——0.890.910.920.890.830.87TEMRA_nm41cg06627009FSTL4NM_0150820.850.890.920.890.860.91TEMRA_nm42cg01186212ANK3NM_0209870.860.850.820.810.830.82TEMRA_nm43cg20940398SYNPONM_0011662080.890.870.880.800.780.83TEMRA_nm44cg04230397MUC21NM_0010109090.850.840.860.820.810.84TEMRA_nm45cg15617591——0.840.910.890.860.840.83TEMRA_nm46cg22112587——0.850.870.900.830.820.90TEMRA_nm47cg15302350LRP5NM_0023350.880.880.890.850.860.89TEMRA_nm48cg19675599——0.890.900.860.860.880.90TEMRA_nm49cg25314245APPNM_2014130.880.880.930.880.860.90TEMRA_nm50cg17037931——0.830.840.840.850.830.85TEMRA_nm51cg11375831SERPINI2NM_0062170.900.880.880.870.860.88TEMRA_nm52cg18766691LPCAT1NM_0248300.900.910.920.850.860.89TEMRA_nm53cg10104542——0.840.820.900.830.800.84TEMRA_nm54cg01071903——0.880.890.900.850.850.84TEMRA_nm55cg12695059——0.930.910.910.850.860.91TEMRA_nm56cg11268546——0.890.880.880.860.850.88TEMRA_nm57cg19277516——0.900.890.870.890.890.88TEMRA_nm58cg25180759MED13LNM_0153350.830.910.920.830.830.89TEMRA_nm59cg16966340——0.880.850.890.860.870.87TEMRA_nm60cg23645373——0.830.890.890.730.740.84TEMRA_nm61cg23642827——0.910.920.900.820.830.86TEMRA_nm62cg27398140PPAP2BNM_003713.40.880.900.900.860.840.90TEMRA_nm63cg26372842OR8S1NM_0010052030.880.880.900.860.870.85TEMRA_nm64cg02936931——0.850.840.800.780.800.87TEMRA_nm65cg10381153CACHD1NM_0209250.900.900.920.880.910.89TEMRA_nm66cg06951647COL4A2NM_0018460.880.870.860.890.850.88TEMRA_nm67cg13177421EPS8NM_0044470.850.800.840.870.790.81CD4+CD4+ ThCD4+ ThCD4+Marker-NKB-ThCD4+CD4+CD4+CentralEffect.NKIDbrightCellsMDSCnaiveact.Th1Th2Mem.Mem.T cellsCD8_nm120.900.920.850.840.800.800.800.850.850.76CD8_nm130.860.840.810.800.790.790.790.840.820.69CD8_nm140.890.840.850.860.760.780.770.820.790.74CD8_nm150.740.720.700.720.690.700.690.710.720.75CD8_nm160.880.760.830.730.590.670.650.640.680.59CD8_nm170.870.700.820.750.560.580.530.610.590.58CD8_nm180.720.710.580.690.570.700.710.700.750.56TEMRA_nm10.930.930.890.930.900.830.870.900.890.79TEMRA_nm20.900.890.860.920.800.690.850.820.790.65TEMRA_nm30.980.980.970.960.950.950.970.970.970.77TEMRA_nm40.900.830.870.930.860.590.750.780.760.53TEMRA_nm50.920.730.860.800.920.920.920.740.550.79TEMRA_nm70.920.900.890.910.810.720.750.760.730.65TEMRA_nm80.800.890.820.700.870.850.890.880.870.67TEMRA_nm90.920.630.870.920.750.720.760.750.740.66TEMRA_nm100.930.810.880.880.700.580.620.710.650.68TEMRA_nm110.950.910.910.940.790.640.710.790.740.62TEMRA_nm120.840.740.860.900.740.650.670.760.680.61TEMRA_nm130.790.900.870.710.730.860.830.730.570.66TEMRA_nm140.910.890.840.930.640.630.640.730.720.60TEMRA_nm150.840.840.870.900.790.720.800.810.770.58TEMRA_nm160.950.930.900.950.830.870.830.860.780.59TEMRA_nm170.900.810.880.900.860.810.830.860.860.70TEMRA_nm180.890.820.870.890.680.600.640.700.660.64TEMRA_nm190.950.870.930.960.880.780.790.850.840.74TEMRA_nm200.890.750.840.890.680.670.740.720.690.58TEMRA_nm210.910.810.870.940.770.590.700.740.670.57TEMRA_nm220.900.710.830.920.740.660.760.730.710.63TEMRA_nm230.910.870.910.930.890.890.820.870.890.81TEMRA_nm240.860.750.850.900.690.580.620.690.650.64TEMRA_nm250.850.640.860.910.810.670.710.720.680.58TEMRA_nm260.900.800.880.900.700.610.640.710.680.66TEMRA_nm270.880.850.890.900.890.840.880.890.830.78TEMRA_nm280.930.810.860.940.680.640.690.760.700.61TEMRA_nm290.820.670.790.890.700.600.700.740.710.59TEMRA_nm300.890.820.880.920.680.820.820.760.730.67TEMRA_nm310.860.830.860.890.730.590.700.720.670.71TEMRA_nm320.820.820.800.860.780.590.680.720.660.61TEMRA_nm330.960.950.930.940.660.570.620.700.630.55TEMRA_nm340.850.810.810.860.650.550.570.660.610.65TEMRA_nm350.880.770.850.900.650.530.590.660.610.57TEMRA_nm360.910.840.890.920.680.620.670.720.660.67TEMRA_nm370.860.880.840.920.860.700.750.790.710.67TEMRA_nm380.840.780.850.870.680.590.640.710.690.67TEMRA_nm390.900.890.890.900.850.800.850.870.840.78TEMRA_nm400.890.750.860.900.780.630.670.670.690.60TEMRA_nm410.930.770.870.920.760.690.790.810.770.76TEMRA_nm420.830.910.820.890.850.710.710.750.620.77TEMRA_nm430.880.810.810.890.740.650.720.730.710.55TEMRA_nm440.850.720.830.870.700.570.610.670.650.60TEMRA_nm450.830.790.860.910.640.560.600.690.620.60TEMRA_nm460.890.800.860.900.750.650.730.790.720.67TEMRA_nm470.890.680.840.900.720.620.660.670.640.56TEMRA_nm480.900.790.890.900.630.520.590.650.630.67TEMRA_nm490.910.880.900.920.870.800.870.880.830.75TEMRA_nm500.830.710.810.860.620.540.570.660.620.67TEMRA_nm510.880.770.870.880.680.600.640.700.650.65TEMRA_nm520.900.640.870.920.770.670.840.700.670.67TEMRA_nm530.840.680.810.900.670.600.730.750.730.70TEMRA_nm540.880.790.870.870.730.640.700.730.690.67TEMRA_nm550.920.920.890.860.780.790.830.850.840.72TEMRA_nm560.870.750.850.880.640.570.630.670.630.59TEMRA_nm570.850.820.850.900.710.550.660.760.660.66TEMRA_nm580.900.840.890.930.840.790.820.840.790.63TEMRA_nm590.810.790.870.910.710.630.690.740.710.64TEMRA_nm600.850.830.830.860.720.630.630.720.650.67TEMRA_nm610.900.800.880.890.780.600.790.770.740.61TEMRA_nm620.900.890.880.900.670.570.590.670.640.62TEMRA_nm630.890.790.860.860.780.580.660.710.710.64TEMRA_nm640.870.690.840.920.650.540.620.690.610.54TEMRA_nm650.920.790.900.920.770.630.710.740.690.67TEMRA_nm660.870.820.860.900.660.570.660.720.660.63TEMRA_nm670.870.790.830.870.650.570.600.710.600.56CD8+CD8+CD8+ThThCyto-CD8+Cen-Ef-CD8+NKMarker-CD4+toxicnaiveCD8+tralfect.NKT-IDTFHT-CellsT8n_1act.Mem.Mem.TEMRAT cellsCellsDiscovery FragmentCD8_nm120.810.080.100.180.290.130.070.230.18TAAAATCTACAGTACACCACAAGGGTCACAATACTGTTGTGCGCACATCG (SEQ ID NO:813)CD8_nm130.820.070.070.150.110.070.050.100.12CGGAAATCAGCTTGGGGGCCTTCTAGCCCTGCAGCTCAGAAAAGTGTCAG (SEQ ID NO:814)CD8_nm140.770.200.220.300.470.390.140.350.39CGAGGTGGATATTAGCAACTCCTTTAGCAGGGCTCAATGGCGTCTTAGAA (SEQ ID NO:815)CD8_nm150.710.150.170.220.200.210.170.250.24TCCAACCAATTGTGCTCTCCCAATTCCAACAACCAAATGAAGCTTCAACG (SEQ ID NO:816)CD8_nm160.610.210.130.450.450.440.290.470.50ATTTTTTACTTTCTATGTGAAATTCATCATCAAATGAGGATTTGCACTCG (SEQ ID NO:817)CD8_nm170.530.190.210.260.390.260.240.290.30GCCCACCGGGGTTGCCCTGGTGTTGCCCCCATCTGTAGAGAAGTTAGGCG (SEQ ID NO:818)CD8_nm180.600.220.250.310.270.280.240.270.27CGCTGTTTTGCTCAGGCTGGCCTTGGGACTCCTGAGCTCCAGTGATCCTC (SEQ ID NO:819)TEMRA_nm10.910.580.860.290.280.190.120.190.33TCTGTCAGAGGGCTGTTGTGGGATTATAAGAGCCCACTTGTGAAATTGCG (SEQ ID NO:820)TEMRA_nm20.830.630.850.380.350.280.110.150.13GTCTTTGCCTGACACCTTCTGTGAGGTTTGCGGGCTTCATTTTAAATCCG (SEQ ID NO:821)TEMRA_nm30.940.890.970.930.760.590.220.420.60CGAGGCGCTGGCGAAGCACGAGGCCTTCTTCATTCGCTGCGGAATCTTCC (SEQ ID NO:822)TEMRA_nm40.870.650.920.560.460.400.120.270.36CGAAAGCAAGCGAGTGAATTAGGATTTCAAAGTGCCCTAATAGTGTGAGT (SEQ ID NO:823)TEMRA_nm50.850.920.920.910.870.890.140.870.85CGGCACAGATAAAAATACAGAGACAATGGTTCCGACCCAGAGATGAGGCT (SEQ IDNO: 824)TEMRA_nm70.830.710.910.460.550.380.140.270.27GTCCGCAGTAATAACAACCAAAGACACATATTCTCAGGCAATGATAACCG (SEQ ID NO:825)TEMRA_nm80.880.720.890.860.830.660.110.740.57CATGAGAAAACTTCTTTAAGACCACCTGTAGAATTCTGCAATCACATACG (SEQ ID NO:826)TEMRA_nm90.780.650.890.440.400.400.120.250.23CGGAAGAATGAAAAGCTAATATTATTGTGTGGCATGATGACTGTCTCTTC (SEQ ID NO:827)TEMRA_nm100.720.720.890.490.590.500.110.470.38CGCCCCACCCCAGAACCAGCTAGCACCCAAGGGCTAGGCAGCCTGCTACT (SEQ ID NO:828)TEMRA_nm110.780.760.920.600.690.550.160.450.42TGCTGTGGGCCTCAGTTTTCCACCTGTTACAGAGAACCCCTCGCCCTTCG (SEQ ID NO:829)TEMRA_nm120.720.720.860.500.470.510.110.410.35CGGGAATCTGTCTGTGTTACAAAGCAACTAGACTCACCCTATTGGCCTAA (SEQ ID NO:830)TEMRA_nm130.800.820.860.730.720.610.120.790.76CGGTCGTTGTAAAAGAGACTGTCTTGAGAGTGAAAAGCAAATAGACATAT (SEQ ID NO:831)TEMRA_nm140.640.680.890.490.490.380.110.250.27CCTTCTCTTCCCCCCAGGCTATGACTTTGCAGCCGTCCTGGAGTGGTTCG (SEQ ID NO:832)TEMRA_nm150.820.700.890.490.420.360.160.340.17GGGGTTATATATTTTTGACCAAATTCACCATTACTCATTTGGCATTTTCG (SEQ ID NO:833)TEMRA_nm160.860.690.910.360.410.430.200.300.40CGCGCAGGGTGGGCGGCTTACCATAGCAAGTGATCCTGCGATAGGGAACG (SEQ ID NO:834)TEMRA_nm170.870.670.850.390.410.350.190.270.27CGGTAGACAAATGATAGACATTTGTTGAATCAAGCTGTGAGTTGGAGATC (SEQ ID NO:835)TEMRA_nm180.640.740.880.470.660.560.130.510.52CGCCACCCCACCTTCATCCACGGACTCCAGGTACTGTAGGGCTGGGAAAG (SEQ ID NO:836)TEMRA_nm190.870.840.950.560.750.580.230.560.49CAGTGACGTGGTGGGGAGCGTGTGCTTGTGTAGGGACAGCTTTCCAGGCG (SEQ ID NO:837)TEMRA_nm200.710.610.860.390.340.290.130.220.20CGTGCCCAGCTTTTCTATGGGAAAAATTGTTCTTCAGACAGAGCATGAAT (SEQ ID NO:838)TEMRA_nm210.820.590.930.320.360.190.160.190.15GCGTACACACCCTGATAAGGTGTCAAGAACCTCCGTTTGAGTACCCCTCG (SEQ ID NO:839)TEMRA_nm220.790.660.890.580.590.450.150.340.30ACTTAGAGCCCACCATGAAGCATCTTTTCTGTTGCTTCACTGACTCACCG (SEQ ID NO:840)TEMRA_nm230.890.820.920.710.730.800.240.630.60GGCCTTCTCTTTCTGGATGGCTGGTCACTGTCTGAGTCCTGATCTGACCG (SEQ ID NO:841)TEMRA_nm240.670.690.860.390.470.400.130.380.34CGGTATTTCAGTTACACTCTGTTGATTCAAAAGAAGGTTGTTTGTCCAAG (SEQ ID NO:842)TEMRA_nm250.850.670.890.620.500.350.150.180.22TTGCTCCAGCACTACAGAGCAGATTTGGAGCAGTCAGGTGGGGAAGCTCG (SEQ IDNO: 843)TEMRA_nm260.750.730.890.510.630.520.160.480.44CGGTCCTCACCTCACTAGATCACCATGACTCACTGGGTAGATGGGCTATT (SEQ ID NO:844)TEMRA_nm270.880.810.880.800.810.740.220.540.60CGCTATTGCTAAGTAAAACCCATGTGTTTTCAGTCATGGTTAGCAGCAGG (SEQ ID NO:845)TEMRA_nm280.680.730.890.420.550.380.160.320.32CGAGGACGAATCTTGAGGCCTCCACTGGICTACACGGACAGAAGCACGCC (SEQ ID NO:346)TEMRA_nm290.720.710.850.390.570.470.110.290.32CGTGGGAAAGTAATACAGGGAGGGAACAGCAGCCCATAAAAAGAACGTTA (SEQ IDNO: 847)TEMRA_nm300.720.800.920.570.570.480.180.560.49CTCATCTTAAGGATGCTTATTATCATAATGCTTTTTATAATTCCTAATCG (SEQ ID NO:848)TEMRA_nm310.740.740.880.450.550.480.150.350.38CTCTTAACCTGGTGGTCTTTCACTAGCTTTACAAAGGTGATACAGTTTCG (SEQ ID NO:849)TEMRA_nm320.790.650.840.580.530.510.120.390.33CGAGGCTCTGCACAGGTAAACTCAAGGGTTACCCTGTGCTTTGAAACCTT (SEQ ID NO:850)TEMRA_nm330.650.760.930.490.490.400.180.350.35TCAGCCCCGGAGGGCAGGCGCCAGTCCATCAGCTTGTATGTCTGTCCTCG (SEQ ID NO:851)TEMRA_nm340.710.590.820.340.350.400.100.250.26CGAGTGTGGAGCTATGATTGGAACCTAGTTCAGGCTCCAAAGCCACACTC (SEQ ID NO:852)TEMRA_nm350.610.690.890.430.580.490.120.440.39CGACCATTCTCACAAGACATTGAACAGAGAATAAGAGGAGAGAAAAAGGC (SEQ ID853)TEMRA_nm360.740.740.920.500.660.570.170.540.46AAGTTCCCATTAGATGACTCACTTCAGGAGGGCAGGAACCATTCTGTTCG (SEQ ID NO:854)TEMRA_nm370.870.750.900.630.730.530.190.400.28CGGCTCTGCCAGGACCCACCAGCCAATTCCAAGTCGAGCAAAAGAATCCA (SEQ ID NO:855)TEMRA_nm380.680.740.830.540.550.560.130.580.49ACTGTTGATCCTGGGAGTCTCTGGCCTTGTATTTATGACTTATCAATTCG (SEQ ID NO:856)TEMRA_nm390.850.870.860.800.830.810.230.790.75ATTCTGTCTAGTCTTTGGTCCCATAGAAATTATTATCTACATCAACCTCG (SEQ ID NO:857)TEMRA_nm400.810.690.910.500.410.460.160.300.33ACACTTCTGGCAAATAGTTCATCTAATTAGAACCATGGGAAACCCCTCCG (SEQ ID NO:858)TEMRA_nm410.760.770.890.500.640.640.190.570.56CGGGGATTCCAACCCCAGGGCACCTCTCTGGCATTCCCATTAAGGAAGCC (SEQ ID NO:859)TEMRA_nm420.810.790.860.670.440.570.160.490.51ATTTGTAACATCACAAGAGTTAGAAGACCCCATATTGCTTGAGCTTTTCG (SEQ ID NO:860)TEMRA_nm430.760.700.830.460.520.430.140.330.35CGAGGCTTGTGCTCTTGGCCACCACTGTCTTCTGGAATTATAGGAGTAAA (SEQ ID NO:861)TEMRA_nm440.730.660.860.420.520.430.130.260.33CGAGTAAAATGATGATCCTCACTCTATGGAAGAGAAGCAGAGCTGGCCCC (SEQ IDNO: 862)TEMRA_nm450.640.720.870.480.500.410.130.400.35CGCCTGGAATTTCTTGAAACACCCTTATACATGCATAAAACTGTAGGTGG (SEQ ID NO:863)TEMRA_nm460.770.640.890.390.460.420.170.310.31CGGTCTTGGGTGGCCCATAGGAGATTAAGAATTTCCTATTATCCAAGCTG (SEQ ID NO:864)TEMRA_nm470.750.650.900.510.520.450.150.460.38CGGCCAGGCTGCAATGCACATGGCCGCCCTCATTGGCAGGGTCACATGAG (SEQ ID NO:865)TEMRA_nm480.650.710.920.410.560.490.150.450.40CGCCACAAATGAGTAAAGCAGGTCTAGCAGGCTTGTCTGTTGAGTTACTG (SEQ ID NO:866)TEMRA_nm490.890.800.900.590.720.610.240.510.55CGAGACACCTGGGGATGAGAATGAACATGCCCATTTCCAGAAAGCCAAAG (SEQ IDNO: 867)TEMRA_nm500.640.710.830.430.550.450.110.470.42CCCCTTTTTCCCAGGGACCCACAGAACTGTGAGCAAGAAATAAATGTTCG (SEQ ID NO:868)TEMRA_nm510.690.740.890.530.680.490.160.500.48CGGTCTCTGCCATTGGTAGGAAAAGTAATGGACTATTTCTGGATAAATCA (SEQ ID NO:869)TEMRA_nm520.830.620.860.450.390.430.190.340.34CGGAATAAAACCACTGAAACACAATCAGGGCTACGTGCATTACCTGTGGC (SEQ ID NO:870)TEMRA_nm530.700.710.880.380.520.560.140.500.45CGGATGCCTATCTGTTCCTGACCCCCAAGGTCCCTCAGGATCTGCTGGGA (SEQ ID NO:871)TEMRA_nm540.730.740.870.570.650.540.170.590.52CGCAAATCCAAACCATATCAGGGTTTCACAGCTAGAGAGAAGGA GTCAAT (SEQ ID NO:872)TEMRA_nm550.790.650.880.390.540.440.220.300.43GGTGATTACAGCAGATGACCCCATCTGCCTGGTGCCTGACTTTATTTTCG (SEQ ID NO:873)TEMRA_nm560.650.710.870.460.590.430.140.420.42GGGGTTGACCATGGCTGGTAACAGGGGACTCTGGTTGGCCAGTGGCATCG (SEQ ID NO:874)TEMRA_nm570.720.760.890.690.720.530.170.440.43CGAGTTTAACCCCACTTGGAGCCAGAAAGATGGGCCAAATCAACACCAAG (SEQ ID NO:875)TEMRA_nm580.850.740.890.540.490.440.220.310.34CACAGACTAATGATAATCTTTGGGAAATTTGGGTCTACCATAAATACTCG (SEQ ID NO:876)TEMRA_nm590.720.700.860.540.690.550.170.410.51AGGTTAAAACCAAGGGCTCAGACTACAGGTGTGTGTAGCATGTGTACACG (SEQ ID NO:877)TEMRA_nm600.700.690.830.500.630.470.140.400.41TTCACTGCAGATGAAATGGGCTTCTCATGCTACCTCAGTTACCAGAATCG (SEQ ID NO:878)TEMRA_nm610.820.590.870.340.370.370.190.240.26CGCATACTTTCAGGGAGAGGCACTATTCTTGGCTTTAAGTTCATGAGTAA (SEQ ID NO:879)TEMRA_nm620.660.720.880.440.650.470.160.380.40CGACAATTTCAATCCAGAGTGTTAAGTGCTGTTACAGAGGAGCTGGGGAG (SEQ ID NO:880)TEMRA_nm630.730.750.870.600.670.590.170.450.45CGTAGTCTGACACAGGAGTCCACTTAGCCATTGATCTGTGTGGCTCAATT (SEQ ID NO:881)TEMRA_nm640.640.610.910.350.350.360.130.200.21GACTGAAACTTGCACCAGTTCTGAATGCCTCTAACCTTGGTTGTATAACG (SEQ ID NO:882)TEMRA_nm650.780.750.930.490.600.500.200.480.40CGAGGCTGAATGAAATCCAATTGGAACTCACTTGAACACTGTTTTGATGT (SEQ ID NO:883)TEMRA_nm660.660.760.870.470.510.490.160.440.40GTGTCCCAGGAAAGGCCCACTAGTGGGTCCCGGTGTGGGACCCACCCCCG (SEQ ID NO:884)TEMRA_nm670.650.670.830.450.450.400.130.360.37ACAGTGAGCTATGCCCTGAATGACAGACACCATATTCACAGGCAAAATCG (SEQ ID NO:885)
TABLE 4DFollicular helper T cells - markerNon-Baso-Eosin-Neutro-Clas-Clas-philophilphilsicalsicalNKMarker-Granu-Granu-Granu-Mono-Mono-clas-IDTargetIDSYMBOLAccessionlocyteslocyteslocytescytescytessicalTFH_nm1cg13077150PRKCZNM_0027440.910.900.910.890.890.88TFH_nm2cg11227141PRKCZNM_0027440.860.820.830.860.850.87TFH_nm3cg27064482MKL2NM_0140480.850.870.890.890.880.84TFH_nm4cg21377860GIMAP8NM_1755710.920.910.910.920.910.92TFH_nm5cg15722603LIFNM_0023090.880.890.900.890.900.80TFH_nm6cg00151768NFATC1NM_0061620.900.910.910.930.870.91TFH_nm7cg15260951NFATC1NM_0061620.940.950.950.950.950.92TFH_nm8cg16421411C2orf48NM_1826260.970.960.970.960.970.96TFH_nm9cg26396261ATXN1NM_0003320.970.950.960.970.970.96TFH_nm10cg10842070DNAJC5NM_0252190.970.980.970.970.970.95TFH_nm11cg09232021MAFNM_1755710.920.910.910.930.920.91TFH_nm12cg13144059SPATS2LNM_0155350.960.970.980.980.970.97TFH_nm13cg26175815TMCC1NM_0010173950.900.900.920.900.880.88TFH_nm14cg07172701SERINC5NM_1782760.910.780.840.840.870.90TFH_nm15cg21911000CD28NM_0061390.880.860.890.910.890.89TFH_nm16cg15213399LPPNM_0055780.920.920.910.900.870.89TFH_nm17cg03596635ABTB1NM_1720280.950.940.950.950.950.94TFH_nm18cg10451262ZHX1NM_0072220.910.910.920.900.910.91TFH_nm19cg01349034——0.900.890.880.880.860.87TFH_nm20cg15873449PTPN2NM_0804230.850.860.870.880.850.86TFH_nm21cg16152136——0.850.890.900.880.890.88TFH_nm22cg20968717LIPCNM_0002360.900.920.920.940.920.91TFH_nm23cg25087423CXCR5NM_0017160.900.920.920.910.900.86TFH_nm24cg08012294CTSBNM_1477800.880.920.920.860.760.91TFH_nm25cg17410313NUB1NM_0161180.920.910.920.910.890.92TFH_nm26cg04337734SCL25A12NM_0037050.890.910.870.880.880.86TFH_nm27cg15039797HIPK2NM_0227400.970.970.980.970.980.25TFH_nm28cg27586885——0.960.950.960.960.950.94TFH_nm29cg20702205RNF216NM_2071110.910.860.910.890.870.91TFH_nm30cg06846719FAM6ANM_0212380.870.880.900.890.870.87TFH_nm31cg23892568CLEC7ANM_0225700.870.880.880.810.820.86TFH_nm32cg24033742——0.900.900.900.900.900.90TFH_nm33cg03280299ST7NM_0184120.820.880.890.840.860.87TFH_nm34cg16375820IL6STNM_1757670.890.860.880.890.870.88TFH_nm35cg11307417ZNF589NM_0160890.880.900.900.870.870.89TFH_nm36cg13774342DLEU1—0.900.920.900.880.910.89TFH_nm37cg21653149ANKFY1NM_0163760.910.910.910.910.920.88TFH_nm38cg14624950SMURF2NM_0227390.870.890.900.900.890.87TFH_nm39cg13142152FAM65B—0.670.780.860.870.850.85TFH_nm40cg15873112ATXN7L1NM_0207250.780.800.840.870.850.86TFH_nm41cg23342358PCBP—0.840.800.760.840.830.86TFH_nm42cg22535163——0.910.900.900.910.900.89TFH_nm43cg13637151PRRC2BNM_0133180.920.920.930.910.910.90TFH_nm44cg26446535ARHGAP35NM_0044910.900.880.900.920.930.91TFH_nm45cg06346099SOD2NM_0006360.470.630.790.840.770.78TFH_nm46cg13049261SETD3NM_0322330.930.920.930.930.920.90TFH_nm47cg06019273ARID1BNM_0175190.850.880.910.880.880.84TFH_nm48cg00780520PVT1NR_0033670.800.780.800.810.850.82TFH_nm49cg07167688——0.950.960.950.960.940.95TFH_nm50cg27168844IL17ANM_0021900.690.890.920.920.890.87TFH_nm51cg18883472CNIH4NM_0141840.910.920.910.920.910.89TFH_nm52cg11887733——0.850.900.900.920.890.88TFH_nm53cg02003272——0.960.960.960.970.960.96TFH_nm54cg20298778PHACTR2NR_0271130.900.920.940.920.890.86TFH_nm55cg19030737ITPKBNM_0022210.740.670.830.810.840.79TFH_nm56cg19324997HDAC4NM_0060370.980.970.980.980.970.79CD4+CD4+ ThCD4+ ThCD4+Marker-NKB-ThCD4+CD4+CD4+CentralEffect.NKIDbrightCellsMDSCnaiveact.Th1Th2Mem.Mem.T cellsTFH_nm10.870.860.850.920.330.630.510.550.540.78TFH_nm20.880.830.810.890.280.600.420.580.570.78TFH_nm30.680.800.170.890.170.660.590.620.630.56TFH_nm40.890.920.900.790.380.730.510.720.710.83TFH_nm50.800.880.840.890.240.350.420.470.440.58TFH_nm60.820.810.880.920.370.710.650.800.740.74TFH_nm70.880.820.920.900.140.290.260.380.290.55TFH_nm80.950.960.930.970.440.680.590.690.690.80TFH_nm90.940.970.960.960.330.870.790.870.850.87TFH_nm100.900.500.940.970.290.870.800.860.870.89TFH_nm110.900.910.900.910.250.560.620.530.470.65TFH_nm120.950.900.960.970.420.880.800.910.850.88TFH_nm130.810.780.880.870.250.540.490.600.560.75TFH_nm140.920.880.840.930.250.630.450.570.620.75TFH_nm150.880.910.870.850.150.380.320.410.250.62TFH_nm160.760.900.840.910.360.880.770.850.860.67TFH_nm170.930.920.910.540.290.620.580.570.580.72TFH_nm180.910.870.890.900.220.490.370.550.450.65TFH_nm190.870.930.880.910.360.730.740.760.700.78TFH_nm200.760.570.850.820.180.560.540.520.520.73TFH_nm210.880.860.870.830.200.400.500.450.420.60TFH_nm220.870.720.890.850.360.630.540.640.620.76TFH_nm230.810.080.850.830.190.590.520.580.580.68TFH_nm240.890.890.800.810.230.460.490.500.450.68TFH_nm250.890.810.890.920.310.660.650.660.650.77TFH_nm260.780.860.860.840.280.740.620.650.610.63TFH_nm270.620.980.910.100.210.520.580.440.450.51TFH_nm280.920.940.890.950.320.810.550.720.690.71TFH_nm290.900.790.890.890.290.800.580.700.780.86TFH_nm300.760.750.830.870.240.580.440.590.590.63TFH_nm310.790.670.810.860.170.380.350.430.290.63TFH_nm320.910.920.890.910.410.720.670.740.770.84TFH_nm330.780.840.850.860.330.620.520.600.610.66TFH_nm340.770.880.800.180.250.690.470.560.660.65TFH_nm350.870.860.850.360.240.570.410.430.540.64TFH_nm360.820.810.880.890.210.450.350.400.390.55TFH_nm370.760.900.860.850.380.700.700.700.700.60TFH_nm380.820.870.850.900.310.610.440.600.520.77TFH_nm390.820.830.810.690.190.420.310.400.330.67TFH_nm400.860.500.810.670.190.480.350.390.410.54TFH_nm410.850.870.830.780.340.710.600.700.720.74TFH_nm420.850.910.890.730.310.650.600.680.530.68TFH_nm430.870.920.880.830.350.760.650.690.730.71TFH_nm440.870.900.890.920.380.650.740.690.630.72TFH_nm450.780.850.770.860.240.450.450.480.440.64TFH_nm460.890.900.870.760.230.480.410.470.420.65TFH_nm470.820.620.870.900.320.540.460.600.600.66TFH_nm480.800.650.770.870.200.420.270.440.370.61TFH_nm490.950.940.930.960.310.530.470.570.500.69TFH_nm500.800.700.860.880.240.720.610.620.600.63TFH_nm510.870.930.890.760.410.760.470.640.710.83TFH_nm520.830.890.830.580.230.400.390.400.440.66TFH_nm530.940.890.920.960.350.580.500.550.570.66TFH_nm540.790.730.890.920.390.790.620.790.710.68TFH_nm550.820.820.800.410.280.680.480.520.590.63TFH_nm560.940.980.930.730.41#DIV/0!#DIV/0!0.700.680.72CD8+CD8+CD8+Cyto-CD8+ThThCD8+NKMarker-CD4+toxicnaiveCD8+CentralEffect.NKT-IDTFHT-CellsT8n_1act.Mem.Mem.TEMRAT cellsCellsDiscovery FragmentTHF_nm10.230.860.860.680.770.820.860.870.86CGTGCTGTGCCCTCGATGCTCCAGCACCTATGGCCCTGCTGACCCTGGAG (SEQ ID NO:886)THF_nm20.180.810.850.670.730.740.720.750.67CGAGGCACGGCCACTTCTCCAAAGGGCCAAGCTTCCCTCGTCAGGCGGCT (SEQ ID NO:887)THF_nm30.080.880.820.700.660.760.810.780.82AGAGAGCTGACAAGGGCATGCACGATTAATTGCACACTCGCACACCCACG (SEQ ID NO:888)THF_nm40.280.880.880.810.900.880.920.910.93CGTAAAGTCTGCTCCAAAGATGGCCTCCAGTTTCGCCACAGCTGTTTTGT (SEQ ID NO:889)THF_nm50.130.780.890.640.710.620.730.650.60CGGGACCAGAAGATCCTCAACCCCAGTGCCCTCAGCCTCCACAGCAAGCT (SEQ ID NO:890)THF_nm60.230.920.850.860.860.900.880.900.90CGGCTCTTCAGGTACAGAGATCTGAACTTGGAAAGACCTGCCTTTCTAAA (SEQ ID NO:891)THF_nm70.100.870.910.630.660.730.930.810.85CGGCTCGCTCAGCCATCAGGTGCCCCACGACACACAGGTGGTTTGGGGGT (SEQ ID NO:892)THF_nm80.320.970.950.870.930.950.950.940.97CGCCCGTCGTTCATGTCGATTCTCTCAGTCAATCAAAACGCTGCCACAGC (SEQ ID NO:893)THF_nm90.160.960.940.930.930.940.960.960.96ATGCAGCGATGTGGCCGGGAGTTAGCATGAAGCGTGGTTATTCTATCACG (SEQ ID NO:894)THF_nm100.160.970.950.850.900.930.960.940.97CGCTGTCCGCCCTTCGCCACCCACCGCGCCTGCTGCTCAGGAATGTTCCA (SEQ ID NO:895)THF_nm110.100.900.910.850.880.620.910.790.73TGTTTCTCTTTACCGTTCAATGCATATGTGCGCAAGCCACCTCTGATGCG (SEQ ID NO:896)THF_nm120.240.980.960.940.950.970.980.960.97GGCAGAGTCATCTGCGTGGCGCACACTGTTGTATATGCTGCACGTACACG (SEQ ID NO:897)THF_nm130.120.840.840.780.720.810.840.870.84GCTTTCTCATTTTTCCGTTCCTCCACCCACTGGCTGGTTATGGGGGTTCG (SEQ ID NO:898)THF_nm140.120.880.900.790.820.870.880.770.88CGTACTTGCAAAGTAATACAGAAACGTGACTTTCGGCAGCTACCCAAGAT (SEQ ID NO:899)THF_nm150.090.820.870.610.770.600.870.790.78CGGTTAATTATGGAAAAACAGCTTGTTAAGCAAATGCTAATGTAAGAAGA (SEQ ID NO:900)THF_nm160.150.930.900.900.740.840.870.800.94GTTTTAATAAAGCACTATCAAAAAGACGGCACAGAGTTTCGGTTGCCACG (SEQ ID NO:901)THF_nm170.150.610.500.770.840.840.870.880.87AGAGGAATCGTGGTGCTTTGCAAATGTGTATCAAGGCCTTTGAATGCACG (SEQ ID NO:902)THF_nm180.120.820.900.680.770.770.690.720.75AAGAAATCCACTAATGAGTGTTCACTAGCACAGGCACATTTATGTTTTCG (SEQ ID NO:903)THF_nm190.160.880.910.820.840.820.840.840.81ACTGCACATATCTTTTTGAAAGACAGCTTTTTAAGGTATGACTCACTACG (SEQ ID NO:904)THF_nm200.110.890.860.710.780.760.840.860.81CGCCAAGTATTCAGCATCTCTTTGGAATTCATTTGTCAGCCTCTCTGGTT (SEQ ID NO:905)THF_nm210.100.830.850.700.800.680.800.690.68CGTCAAGCTGGCAGAATTTTAGAGGCATCTCATTTAAATTAGATCTGGCC (SEQ ID NO:906)THF_nm220.160.860.890.730.830.800.890.900.89CGGGTGACTCATAGAGAGTGATTAGAAGTAAAAAGGTTCTGGAAATTCCC (SEQ ID NO:907)THF_nm230.100.840.820.540.810.770.830.850.81TGATGAGTTGTGAGGCAGGTCGCGGCCCTACTGCCTCAGGAGACGATGCG (SEQ ID NO:908)THF_nm240.150.900.890.850.910.880.890.900.88CGCCTAACCAGTTGGAAACAGGGCTGTCCTGAGCCAACACCCAGGAGAGC (SEQ ID NO:909)THF_nm250.190.890.890.840.890.870.870.890.84CGGTAGAGTCTAATTTGCAAGATGTAAATGCAGAAAATAGACATTTCAGC (SEQ ID NO:910)THF_nm260.150.870.840.840.790.770.820.810.81CGACGGACACTAAAACTGGGTCAGAAAACTTGGGTTCTAAACTCCTGTGC (SEQ ID NO:911)THF_nm270.090.600.600.870.870.830.960.870.85CGGTACCATGATACGTGCCGCAGAATGTTCCTGCTGCGACCGTAAAGAAC (SEQ ID NO:912)THF_nm280.200.910.930.740.810.800.840.770.83CGCCCGCGCCTTTCCCAGGCTCAAGGCCTCCCTGCCCACCAGGCAGGTGG (SEQ ID NO:913)THF_nm290.210.900.880.850.900.890.900.890.90CACTAGTAACTCTCCGGTGTCTAGAGTTAGTACTGATGGACTCCCTGCCG (SEQ ID NO:914)THF_nm300.120.800.840.690.590.770.690.820.76CGCTGAGATTGTTTGAGTTGTTTTTCTTAATTAGTATTTCATAGCTAAGT (SEQ ID NO: 915)THF_nm310.110.850.870.790.800.690.830.810.80CGGTTAAATTAATTAATGTCAGACTTAGTTGTGAGAGTAATGAAGGCAGC (SEQ ID NO:916)THF_nm320.220.900.890.790.870.900.890.880.90CGCTGGGAGAACTTGAGCGGGGAGCCCAGCACCACACACCCACTTGCCTC (SEQ ID NO:917)THF_nm330.160.850.800.820.690.770.850.810.83CTGCTCTAGGAATATATTTACATACATGTATTTCTCCTATTTCTTCATCG (SEQ ID NO:918)THF_nm340.140.720.590.810.760.840.840.860.90CGGGGAATCCCTCCCTGCCACTGTAGAGGATTTATGGGTTGCCCTTAAGT (SEQ ID NO:919)THF_nm350.160.730.690.770.820.830.890.860.87GAGTGTATCCTCTGATGTACACTAAGAGCGGACTTGAGGCTAAAGTTTCG (SEQ ID NO:920)THF_nm360.130.810.890.610.690.660.600.620.63TGGGAGACTTGTAATTGTGTACCTGTTTGCATTGTTTAGCCTATGCATCG (SEQ ID NO:921)THF_nm370.190.860.850.780.720.770.840.800.79CGGTGCTTGAGGAAGATGCATCTGCTCTTGACACTGACATACTCGAAGGA (SEQ ID NO:922)THF_nm380.180.850.860.760.770.780.760.730.76CGGCATCCGAATATTCTAGCCCTGGCAGACCTCTTAGCTGCTTTGTTGAT (SEQ ID NO:923)THF_nm390.130.840.810.650.810.760.740.740.79TCCCAATCAGTGAGACCTCAAATAATGAACTTGGCTCTCATTTATACACG (SEQ ID NO:924)THF_nm400.120.790.870.730.790.690.730.710.65ATTCAAAGACGCTTGCTCTGAAAGCCCGAAATTCAGTCTTTCTGAAGACG (SEQ ID NO:925)THF_nm410.190.830.830.780.770.800.830.810.80TACCAGAGTGCCTGTGCTGTTGTATCCTGACACACCAGGTACTGCATACG (SEQ ID NO:926)THF_nm420.230.850.820.840.840.830.900.860.81CGCACAAAAATGTAGAAAGAATATTGGAGACGGAAAATTGTGAATGTACC (SEQ ID NO:927)THF_nm430.250.900.860.830.850.860.890.870.90GGAAATCGAATCGTGGATTCACCAGGCCGGTGCTGGCACACTCACCCTCG (SEQ ID NO:928)THF_nm440.250.890.860.810.820.800.840.850.85GTTGTCAGAATTTCCTTCCCTTTAAAGGCTGAATAGGCCAGGCGTGATCG (SEQ ID NO:929)THF_nm450.120.800.840.770.800.740.760.710.69CCACTACAAAAACAGTCATAAAGAGCTTAACATACTCAGCATAACGATCG (SEQ ID NO:930)THF_nm460.180.780.890.610.660.620.620.620.62CGATGGGTAGGTGGAATAACAGCCCCCTCCCAAAGCTTAGCAACAACAGC (SEQ ID NO:931)THF_nm470.180.810.830.740.710.770.780.780.79AGAATGGAAAATGTAAATTAAGCCTTTGTTTTCCATCATCATTCTCATCG (SEQ ID NO:932)THF_nm480.110.730.830.560.670.690.670.730.76CGCCACCTCCATGCTGIGTTTCTGTGGCTGGAGCTTTTCTGCACTGGAAA (SEQ ID NO:933)THF_nm490.260.880.950.710.800.830.560.880.79TGCCTGAGGCCGCCCGCTGTTCAGCGGAAGAGCCAACATCTGTGCTATCG (SEQ ID NO:934)THF_nm500.190.840.870.760.810.620.780.660.63CGGTCCAGAAATACTATCTGGTCCAAATCAGCAAGAGCATCGCACGTTAG (SEQ ID NO:935)THF_nm510.260.850.850.850.890.870.890.890.89AATTACCCTCATGATGAACATTTCCCTACTCTGAGTAAAGATGCTATCCG (SEQ ID NO:936)THF_nm520.170.760.880.580.690.660.760.800.75TAAATAAAGATCATCTGGTCCAAGGATGGCAAATATGTGGCACAAGTACG (SEQ ID NO:937)THF_nm530.270.900.960.650.620.800.860.840.89AAGGCGCAGCCAAGGACTATTACACCTCTGGCTGCTCGGACGCATCTTCG (SEQ ID NO:938)THF_nm540.230.860.910.670.740.740.900.760.78CGGGTGGCTGAATGGAAAAACAAATGGGGCTTCACCTGTGACTCAGACCA (SEQ ID NO:939)THF_nm550.160.690.600.690.630.820.850.790.86CGGCTCAGGAGACTGAAACATCCAAAGCCTGAATTGGTCCTTATATCATG (SEQ ID NO:940)THF_nm560.290.910.840.870.810.850.970.890.92CGCCCCGCACGTACTGTGTGCCTCGTTCTTTATCTGTGTTCGTTTATTCA (SEQ ID NO:941)
TABLE 4ECD4 positive T cell MarkerBaso-Eosin-philophilNeutrophilNon-Marker-Granu-Granu-Granu-ClassicalclassicalIDTargetIDSYMBOLAccessionlocyteslocyteslocytesMonocytesMonocytesnCD4-nm1cg24885723CA6NM_0012150.910.930.900.920.91nCD4_nm2cg26280976——0.920.920.940.930.92nCD4_nm3cg00912164——0.890.900.900.910.89nCD4_nm4cg04116345MANIC1NM_0203790.890.870.880.880.88nCD4_nm5cg13484324——0.920.920.870.910.92nCD4_nm6cg10555744MANIC1NM_0203790.880.900.930.910.92nCD4_nm7cg08639389STIM2NM_0011691170.910.920.920.930.92nCD_meth1cg25737313——0.040.030.030.030.03nCD_meth1cg13921921ARHGEF2NM_0047230.210.250.050.030.05nCD_meth1cg03290131DUSP5NM_0044190.100.150.080.020.03nCD_meth1cg04742550ITGAXNM_0008870.000.010.010.010.01nCD_meth1cg21268578GGA1NM_0010015600.030.030.040.030.02CD4mem_nm1cg11106864RAP1GDS1NM_0011004270.800.920.880.890.89CD4mem_nm2cg08877853GPR63NM_0011439570.850.850.890.880.90CD4mem_nm3cg14108380SDCCAG3NM_0010397080.950.950.940.960.96CD4mem_nm4cg10328548SS18L1NM_1989350.920.920.910.930.92CD4mem_nm5cg03188793TALDO1NM_0067550.820.710.840.870.86CD4mem_nm6cg09187865——0.910.910.820.800.80CD4mem_nm7cg04936610FAM38ANM_0011428640.780.820.830.840.86CD4mem_nm8cg21685655PON2NM_0003050.840.860.870.850.85CD4mem_nm9cg21132587ALLCNM_0184360.960.960.970.970.96CD4mem_nm10cg04026937HLA-NM_0021240.780.760.740.760.72DRB1CD4mem_nm11cg18591489——0.910.910.910.900.89CD4mem_nm12cg26296371FARS2NM_0065670.750.820.760.800.75CD4mem_nm13cg26899005HCFC1NM_0053340.890.890.910.900.93CD4mem_nm14cg08299859——0.930.940.930.940.93CD4mem_nm15cg05450979NUBP1NM_0024840.730.700.780.770.68CD4mem_nm16cg15700429HLA-NR_0012980.790.880.890.880.85DRB6CD4mem_nm17cg25232888OSBPL5NM_0011440630.790.740.900.920.92CD4mem_nm18cg05606115——0.860.890.910.920.92CD4mem_nm19cg15654485HLA-NR_0012980.870.860.890.900.90DRB6CD4mem_nm20cg20601736ERICH1NM_2073320.880.880.880.900.87CD4mem_nm21cg01419713PLATNM_0009300.870.910.910.900.89CD4mem_nm22cg13213216KIAA1210NM_0207210.950.950.970.970.96CD4mem_nm23cg23812489FLG2NM_0010143420.920.910.920.900.91CD4mem_nm24cg08916385GNRHRNM_0004060.910.880.900.890.87CD4mem_nm25cg13011976PAGE2BNM_0010150380.870.890.870.890.88CD4mem_nm26cg09354553——0.940.950.930.940.92CD4mem_nm27cg00944599TRRAPNM_0034960.860.830.880.870.82CD4mem_nm28cg07904290——0.960.980.970.970.97CD4mem_nm29cg22626897SMYD3NM_0011677400.910.910.910.900.91CD4mem_nm30cg18887230SMURF1NM_0204290.890.890.890.890.87CD4mem_nm31cg16490805——0.790.630.710.730.71CD4mem_nm32cg18203203——0.710.730.740.700.71CD4mem_nm33cg22951524AHRRNM_0207310.820.830.840.840.84CD4mem_nm34cg07712165TBCDNM_0059930.900.900.910.910.91CD4mem_nm35cg01201914——0.820.820.830.820.82CD4mem_nm36cg07951602——0.820.850.820.840.83CD4mem_nm37cg21498326——0.860.890.870.890.83CD4mem_nm38cg11791078RANBP3LNM_1450000.820.700.740.750.76CD4mem_nm39cg15613905MCCNM_0023870.760.800.810.820.82CD4mem_nm40cg09307431——0.870.860.860.860.87CD4mem_nm41cg21911000CD28NM_0061390.880.860.890.910.89CD4mem_nm42cg20770572HLA-DQB1NM_0021230.870.870.880.870.86CD4mem_nm43cg22787186——0.620.650.840.800.81CD4+CD4+CD8+CD4+ThThCyto-Marker-ThCD4+CD4+CentralEffect.toxicNK T-DiscoveryID naive Th1 Th2Mem.Mem.T-CellsCellsFragmentnCD4-nm10.180.850.890.820.900.540.92CGGATAGATTAGTTCTGGAATAATGCCTGAGACACAGCACCCAGAACCTC (SEQ IDNO: 942)nCD4_nm20.210.870.830.770.880.680.92TGTTGTGGGAAGCTTTCCCGTGCGCTGTAGGATGTTTAGCAGCACCCTCG (SEQ ID NO: 943)nCD4_nm30.190.810.720.750.870.520.91GTACTCTTACACTCACGGGGGTGCCGGGCCCCTGGAACCTGCAACTCACG (SEQ ID NO: 944)nCD4_nm40.160.740.570.590.750.570.89CGGAATTTTTTAGTGCAAAATATTTACTAGTGTGAGGCAGAACATTATTA (SEQ ID NO: 945)nCD4_nm50.220.880.780.660.740.660.92CGAGTCTATGTAATTAAGAGACTGAGAATTACACTAGGGACCTCCTATAG (SEQ ID NO: 946)nCD4_nm60.200.810.680.650.810.540.93GTAGCTAAGTAAGGGGCATTCATTTCTCCCTTTCTTGTTAAGGAACTACG (SEQ ID NO: 947)nCD4_nm70.190.690.620.590.600.550.87CATACTTCAAACATAACGTGTCTTAAAACAACTTTTGATCTCTGTCACCG (SEQ ID NO: 948)nCD_meth10.610.140.140.240.150.350.07CGCCCCCGCGGGGCCCAGCCAGATGTCAGCTGCAGTTATTAGCCTGGGCG (SEQ ID NO: 949)nCD_meth10.690.160.350.340.290.430.05CGTGTCTTGATTCCACCTTTAGAGGCTGCCCAGGGTTTCACACCCGACCC (SEQ ID NO: 950)nCD_meth10.630.070.190.250.160.420.05CGAGCCTGTGGCTTTCAAGCTGTGGACATCTGGCCTAGCTAGATTTCTAC (SEQ ID NO: 951)nCD_meth10.690.140.160.270.170.110.01CGCAACTGATCCGAGGACAGGCTCGGCCTCCCACACGCCCCCACCCCCCA (SEQ ID NO: 952)nCD_meth10.740.240.230.320.250.170.04GTCTCCTTCATTCATTGGCCTCTGCTGGGGCCTCCTATGGGTGTCTTACG (SEQ ID NO:953)CD4mem_nm10.920.900.910.470.020.890.85CCATACCACTTGTGCATGCATGTGATGTTCTAATACCAATTGAAGAACCG (SEQ ID NO: 954)CD4mem_nm20.930.870.870.440.030.910.83GGCAGTGTTGACTGCGTTCCATACCGGGACATCCAACACAACATTTGTCG (SEQ ID NO: 955)CD4mem_nm30.920.110.080.260.130.670.59CGGATGCCCTCGTGGGCCAGCTATCCCCAGGCACAGCGAGACAGCGACGT (SEQ ID NO: 956)CD4mem_nm40.940.900.900.480.110.930.93CCACCGTGCCCAGCTCTTTTCTTTCTCTAAGAATCCTCTGGCATTCTGCG (SEQ ID NO:957)CD4mem_nm50.730.910.910.460.030.910.88CTCACTCCCATGCTGTTACAGGTCACCTCTTGCAGGGGCATATTTGATCG (SEQ ID NO: 958)CD4mem_nm60.870.930.920.500.120.940.90AAATATTACCTATTAGATTGGTAACAATGAAAAAGACTTGGCAGCCGCCG (SEQ ID NO: 959)CD4mem_nm70.880.850.850.440.060.860.80CGCCAACAGAGGATGGCCAGCCCCACCCCAGAGGACAGCGCACCCACGGC (SEQ IDNO: 960)CD4mem_nm80.830.750.730.460.040.860.87CGTTATCAGTAGTTCTAAACAGCCATAGTAGTCACAGTGCCAGAAGTGAG (SEQ ID NO: 961)CD4mem_nm90.970.970.980.550.310.970.98GCCGGGCGAGCTGAGATCAGACAACAGGCGCTGGACGCATCCTAACTACG (SEQ IDNO: 962)CD4mem_nm100.880.750.750.460.060.840.76GGAAGTCAGAAAGCTGCTCACTCCATTCCACTGTGAGAGGGCTTGTCACG (SEQ ID NO: 963)CD4mem_nm110.690.180.090.270.150.700.57TGTGAGTTAGTTCTACAGCACAATGCTTGGCTGCTGTTTCAGCAATTGCG (SEQ ID NO: 964)CD4mem_nm120.790.550.530.450.040.700.72CGACTTCCCAGCCAAGGGAAACTGTCACCGAGGGTGGGACTAAATCTGAC (SEQ ID NO: 965)CD4mem_nm130.730.560.570.200.170.760.71CGCGCGCCTATTGATTTGTTTCTGAGGAGAGTACACCGTTCACTATTGTA (SEQ ID NO: 966)CD4mem_nm140.930.940.940.590.140.930.93TCTGCGTATTCCTTTCTGTTCTTTAAAAATGTTAAACCATGGGGTGCTCG (SEQ ID NO:967)CD4mem_nm150.830.820.810.480.030.820.69CGCCCCACACTGGGGTCACCCACCTATGAGCGGATCCAGGGGCACTCTGC (SEQ ID NO: 968)CD4mem_nm160.740.760.800.390.130.720.72TTCCTCAGCTCCTGTTCTTGGCCTGAAACCCCACAGCCTTGATGGCAGCG (SEQ ID NO: 969)CD4mem_nm170.970.940.940.520.190.950.86CGTACAGAGCCTTAAACCACATCGTGGCGGTGCCGTCTGAGCTGTAGCGG (SEQ ID NO: 970)CD4mem_nm180.900.880.850.490.160.860.80CTTTTCCTTGCTAAATCAATTCCCTAAGACATCAGGACTGTGAGACATCG (SEQ ID NO: 971)CD4mem_nm190.890.870.880.440.180.870.90CTCATATAACCCCAAGAGGTAAATTAGTATAATTTAACCTACATTATACG (SEQ ID NO: 972)CD4mem_nm200.870.830.820.430.170.870.83CAGAAACCTCACACTCAATTAGCGAGACTGCAAACACTCTGTATTAACCG (SEQ ID NO: 973)CD4mem_nm210.810.140.160.220.190.720.68CGCCTCCCACCCCTGGCAGGCTGCCATCTTTGCCAAGCACAGGAGGTCGC (SEQ ID NO: 974)CD4mem_nm220.960.960.960.590.260.960.95ATCATTGTTCTCTCCGTGCAGCTAGGTATGCCGCAAGGTCTCGGGTTCCG (SEQ ID NO: 975)CD4mem_nm230.920.910.910.510.190.920.90CATTTTCCCAAGGGTCCAGGCCCTAAACATGCCAGACTACCAGTGGATCG (SEQ ID NO: 976)CD4mem_nm240.920.530.510.180.270.880.83CGCATTTGAGGAGCTCTAAGTTGTTGAATCTAAGTTGTTGGATGAGTCAA (SEQ ID NO: 977)CD4mem_nm250.830.370.300.250.190.770.69CGTTGTCAGGAGCGCTGGTGGTTTAGGTTCTCCACAGACGCAGGAAAACA (SEQ IDNO: 978)CD4mem_nm260.910.900.930.610.200.930.70CGCCAACACAGACGAACCCCAACACGTGGCAAACCCCAACACAGGCGAAC (SEQ IDNO: 979)CD4mem_nm270.720.150.200.240.160.810.66TCCTCAACATGGTATGGGGTTCGCTATCACCAGCGTGAAGATGGAAACG (SEQ ID NO: 980)CD4mem_nm280.970.970.960.200.460.950.93CGATGACTAATTTGGTTAGCGGCAACAACAGGCTTCTTGCGGCGAGGCCT (SEQ ID NO: 981)CD4mem_nm290.880.890.870.540.230.900.89CGGCGTGTGTCTTTGTTGAATGCCTTATTGAGGTCACACACTCTATGCTT (SEQ ID NO: 982)CD4mem_nm300.710.240.150.260.210.710.68CGGCCATCCTGCTTTAGGGATGAATTGAAACTGGAAAGAGAGTAGTACCA (SEQ IDNO: 983)CD4mem_nm310.830.700.690.280.050.860.83TGAGAAGGGGCACCCAATGTGCTTCCTCTTGGGGTGCAGCGGTGTGGCCG (SEQ ID NO: 984)CD4mem_nm320.760.520.560.210.040.770.67CGCACACACATACTTGCATGTGGATGCAAACACAATTGGTGCATGGGTTT (SEQ ID NO: 985)CD4mem_nm330.830.740.750.430.160.800.71CGCATCTGAGCGTAGACACACAGATCTGAGCTTGGATGGTGGTCACTGCG (SEQ ID NO: 986)CD4mem_nm340.910.910.910.220.440.910.90CAGAAGGTCACACAGACGGTTGCGCTGCTCTCTCACCACTGCAAGCTCCG (SEQ ID NO: 987)CD4mem_nm350.870.460.870.420.160.840.82CGCCTAGGCTCAAGCAATCTGGCTCTGGATGTCTTTAACTTGTGATTGAA (SEQ ID NO: 988)CD4mem_nm360.880.780.790.200.170.800.70CGCCTCTCAAGAGCACGATGTAAGGGCTCCAAGATGAGTTTGGGCTTCCC (SEQ ID NO: 989)CD4mem_nm370.880.140.180.350.240.740.59CGGTTAAACATTGGTATAGAAACCAGATCTACTTTTAATTGAAATCAGAC (SEQ ID NO: 990)CD4mem_nm380.610.660.600.070.090.650.71CGGAAAAGGAGCTTGTCTTGAGAAACAACAAAGAATTGAGCTATAGTTTC (SEQ ID NO: 991)CD4mem_nm390.840.440.440.100.330.740.61TGCAGTTAGGACTCCATAGCAGGCCTGCAGTGGCCCTGGTGATAACCTCG (SEQ ID NO: 992)CD4mem_nm400.810.190.240.330.260.660.53AGGAAGCCTTTAAAGGACTGGACCCGGAAAGCACCTACTAAAGTGTATCG (SEQ IDNO: 993)CD4mem_nm410.850.380.320.410.250.820.78CGGTTAATTATGGAAAAACAGCTTGTTAAGCAAATGCTAATGTAAGAAGA (SEQ ID NO: 994)CD4mem_nm420.880.830.830.270.420.830.79CGGTGACAGATTTCTATCCAGGCCAGATCAAAGTCCGGTGGTTTCGGAAT (SEQ ID NO: 995)CD4mem_nm430.840.850.830.270.250.800.82CGGTACCTCTACTGCTGAGTCCAAAGTCACCGCGGCATACCCAGCTCGGC (SEQ ID NO: 996)
TABLE 4FMonocytes-MarkersNon-Baso-Eosin-Neutro-Clas-clas-philphilphilsicalsicalNKMarker-Granu-Granu-Granu-Mono-Mono-clas-IDTargetIDSYMBOLAccessionlocyteslocyteslocytescytescytessicalMOC_nm21cg23244761PARK2NM_0045620.960.960.970.030.060.97MOC_nm22cg13430807MTMR11NM_1818730.840.840.860.030.070.89MOC_nm23cg05923857TCF7L2NM_0011462840.790.820.810.020.080.92MOC_nm24cg01041239LDLRAD4NM_1814820.760.850.770.030.080.93(C18orf1)MOC_nm25cg21459713ERICH1NM_2073320.900.920.940.080.140.91MOC_nm26cg12655112EHD4NM_1392650.960.820.680.010.040.97MOC_nm27cg10480329CENPANM_0018090.910.860.840.070.090.94MOC_nm28cg14428166MYOFNM_1333370.940.920.850.110.110.95MOC_nm29cg25898577PPM1FNM_0146340.890.850.730.060.070.84MOC_nm30cg16636767FAR1NM_0322280.910.920.910.100.150.92MOC_nm31cg02244028SCN11ANM_0141390.890.900.860.130.120.88MOC_nm32cg07213487TRRAPNM_0034960.900.910.910.100.130.90MOC_nm33cg03963853MGRN1NM_0152460.980.970.970.260.270.97MOC_nm34cg22056336RBM47NM_0190270.900.890.870.180.160.85MOC_nm35cg18066690KIAA0146NM_0010803940.920.910.910.060.100.91MOC_nm36cg00101629KAZNNM_2016280.900.890.840.110.140.88(KIAA1-26)MOC_nm37cg20918393RIN2—0.970.970.900.210.120.98MOC_nm38cg10732094ERCC1—0.860.810.760.130.090.87ncMOC_nm1cg04143805ANKRD11NM_0132750.880.880.890.820.320.91ncMOC_nm3cg07004744ERICH1NM_2073320.950.940.930.930.390.96ncMOC_nm6cg07369606SECTM1NM_0030040.890.890.930.910.480.95ncMOC_nm8cg02029908DUSP1NM_0044170.930.940.940.920.230.93ncMOC_nm9cg16908740——0.910.860.900.850.180.93ncMOC_nm10cg08969823——0.960.940.940.960.300.95ncMOC_nm11cg14684854——0.910.900.910.910.260.88ncMOC_nm12cg24534048——0.980.970.960.820.180.98ncMOC_nm13cg19683800CYB561NM_0010179170.900.760.850.870.240.93ncMOC_nm15cg08376310KCNQ1NM_0002180.880.790.910.810.190.98ncMOC_nm19cg07457429——0.910.910.920.870.290.92ncMOC_nm20cg10492417FANCANM_0001350.860.890.900.830.250.88ncMOC_nm21cg01742428FAM26FNM_0010109190.910.920.920.910.360.92ncMOC_nm22cg19586199PRKACANM_2075180.910.930.970.960.450.98ncMOC_nm24cg10143416——0.930.950.940.950.460.95ncMOC_nm25cg03263792TSPAN16NM_0124660.870.770.790.850.370.86ncMOC_nm26cg09779405——0.860.830.810.730.250.85ncMOC_nm27cg16288101——0.900.850.850.740.260.88ncMOC_nm28cg20380448NAAANM_0010424020.800.810.770.830.350.83ncMOC_nm29cg05390144ELF5NM_0014220.870.880.880.870.420.88ncMOC_nm30cg13187188GPR152NM_2069970.880.880.880.880.440.95ncMOC_nm31cg04322596TCF7L2NM_0011462840.930.900.900.920.490.92ncMOC_nm32cg07744832UHRF1BP1LNM_0010069470.870.880.890.890.480.86ncMOC_nm33cg13318914DDAH2NM_0139740.870.800.840.800.390.89ncMOC_nm34cg14439774SMG6NM_0175750.870.830.860.870.460.81ncMOC_nm35cg15896579——0.800.720.750.760.360.76ncMOC_nm36cg09736194LOC285740NR_0271130.880.750.850.870.490.91ncMOC_nm37cg18898336RGS12NM_1982290.890.880.890.850.460.88ncMOC_nm38cg09262230TMEM181NM_0208230.940.950.960.950.570.95ncMOC_nm39cg10794991——0.970.950.970.840.460.96ncMOC_nm40cg02667577WIPI2NM_0160030.850.840.880.850.280.58ncMOC_nm42cg06070445BCL6NM_0017060.880.690.690.700.180.86ncMOC_nm44cg24143729RASA3NM_0073680.860.850.840.670.250.86ncMOC_nm46cg11129609WDR46NM_0054520.790.600.520.580.130.67ncMOC_nm48cg02317313LOC338799NR_0028090.800.570.770.610.210.89ncMOC_nm50cg04690793SNRPCNR_0294720.890.400.770.750.110.85CD4+CD8+ThCD4+Cyto-CD4+Cen-ThtoxicMarker-B-ThCD4+CD4+tralEffect.T-NK T-IDCellsnaiveTh1Th2Mem.Mem.CellsCellsDiscovery FragmentMOC_nm210.980.980.980.990.990.980.970.98TGGGATGGAACGGCTGCGACAGATCTCCATTAAAGCCAGCGCGTCGTTCG(SEQ ID NO: 997)MOC_nm220.820.860.870.900.890.890.900.86TTCTTGGACCCCTCTTCTTTGTCCCTTCTTCCTCTTTATCACCCAGAGCG(SEQ ID NO: 998)MOC_nm230.920.800.830.840.800.840.900.90CGGCCATCAACCAGATCCTTGGGCGGAGGGTAGGTGACGCCCTTCTCAGG(SEQ ID NO: 999)MOC_nm240.830.750.940.950.890.950.750.89CGCCGCTCATGGGCCTGGTGTGCATGCAGCTGCGCAGAGGGCCTCTGCCT(SEQ ID NO: 1000)MOC_nm250.930.920.840.900.890.910.920.89TTGTGAGGAGGATGGTGTGGACACCAGCGAGGAAGACCCGACACTGGCCG(SEQ ID NO: 1001)MOC_nm260.880.950.900.800.870.800.970.96AGAGAAACTCCACGCCCACTAACAGTCATTCTCTATTTCGTTTGCATGCG(SEQ ID NO: 1002)MOC_nm270.910.930.930.940.930.930.930.92CGATCTTAAGAGAAAGGGCAGGAGTGTTTCCTTGACCCCACATTCTCACT(SEQ ID NO: 1003)MOC_nm280.950.950.930.950.950.950.960.95CGCCCCCGGGGTAGCGGCTCTCGTTCTGATAGACTTCATCAGTGAACTCC(SEQ ID NO: 1004)MOC_nm290.910.890.880.880.870.880.920.89CGCTGATCCAGTCACCGGGGAGGGGCTGACTGGCAGCCACACAGAGGTTT(SEQ ID NO: 1005)MOC_nm300.880.900.920.920.920.920.900.90CGGTTCCCAATTTGAAGAGTGGAGACAGAAGTCAAGAAAATAAGCTTTTCSEQ ID NO: 1006)MOC_nm310.910.910.890.880.890.900.910.88CGGCTCAGCCTTATTGTCTTGCTTAATGTCTGGGTCTCAGTTTTAGAGAC (SEQ ID NO: 1007)MOC_nm320.600.920.900.890.900.900.920.92TGTGAAGCAGCTAGAGGCGCGCTGGAAACCTGATGCATGCTGCTGCCTCG(SEQ ID NO: 1008)MOC_nm330.980.980.990.980.980.980.970.98TGGCCACGGGTCATTCGTGGTTCCCCTGGAGCCTTGCGGTGTATAGAGCG(SEQ ID NO: 1009)MOC_nm340.750.880.810.830.840.830.870.82CGTGAACTTCCTAGAGGCCAAAGTAAAAATAAAAACAGGGTCGCTAACAT(SEQ ID NO: 1010)MOC_nm350.910.930.910.920.940.910.920.91CGGAAGGTGAGTGGGCAATGAAATGTCCAATTTTAAAAGAAATTCCACGT(SEQ ID NO: 1011)MOC_nm360.750.920.830.860.850.850.860.69CGCAAGAATGCACTTAGTTAATCCAACAAGTATTTATTCAGTGCCTGAGT(SEQ ID NO: 1012)MOC_nm370.980.980.980.980.980.980.980.98TTTCAACAACACCACTGAAAGAATGTAAACGGAGCTGGTCGCGTTGGTCG(SEQ ID NO: 1013)MOC_nm380.710.870.880.880.890.900.900.87GAGGAAGTCCTTTCTGGAGTCTGACCCTCAGTCTGCCTGCTTCAAATGCG(SEQ ID NO: 1014)ncMOC_nm10.880.900.880.880.890.880.890.87CGAAATCAGCGGAGGCCCCTGCTGAGTGAGTGGACACACCCAGGCGCACG(SEQ ID NO: 1015)ncMOC_nm30.950.940.960.960.950.970.960.95AACATGAGCAGCATGGACAACGCGGTACAACGGGGCGAGAGCGCCAACCG(SEQ ID NO: 1016)ncMOC_nm60.950.890.880.890.900.900.930.88CGCAGGCTTGGAGCCATGCCAGTGACACGCCTAGGAAAGTTCACGCACCG(SEQ ID NO: 1017)ncMOC_nm80.930.930.920.910.890.890.940.88CCCACTATATATTGGTCCCGAATGTGCTGAGTTCAGCAAATGTCTTGACG(SEQ ID NO: 1018)ncMOC_nm90.920.910.880.900.900.900.910.89CGGAAGAACACTTGTATATGCTGACATCAGCAAGCAAAATGCATACAGTT(SEQ ID NO: 1019)ncMOC_nm100.970.960.960.950.970.960.960.95GGCTTCCGGTGACCAGGATAGGAAGTGTTGCAGGCCCTGCCCCGAGGGCG(SEQ ID NO: 1020)ncMOC_nm110.880.910.840.840.860.850.890.84CGCCGAGCTCAGCAGAAACCCGCCCAGAAGGTCAAGGACCAGCAAAAGGG(SEQ ID NO: 1021)ncMOC_nm120.970.980.970.970.970.980.980.98GAGGCCTGGCACGGCGGCACCGGAAGCGGGTACTGGTGCCCTAAGGAGCG(SEQ ID NO: 1022)ncMOC_nm130.920.860.910.920.940.930.940.94TGCGGGCCTCTCCTGCCCTTTGTACTCCACGAGGTGTGAGGAAGTTGCCG(SEQ ID NO: 1023)ncMOC_nm150.940.840.980.970.980.980.980.97CGCGCTCACAGCCTCCGTTCCCAGACACGCCCGGGCCTGAGCCCCCAGGC(SEQ ID NO: 1024)ncMOC_nm190.920.920.920.910.910.900.930.90CGGTCATAGTCCTCTGGAGTTGACATCAGTGGGACCTCGGTGAAACTGCA(SEQ ID NO: 1025)ncMOC_nm200.900.890.750.730.780.770.870.86CGCTGTCCGGAACTGGGGTGCTCCACCCACACTGTCTGGAACTGGCACAG(SEQ ID NO: 1026)ncMOC_nm210.930.920.920.910.930.930.920.94CGCCCATCATAGAAGTACCAGAACTTGAGCTGGACTTTGCTGATTTAGCT(SEQ ID NO: 1027)ncMOC_nm220.980.910.970.950.970.980.970.97CGCGGTTGCGCTAAGGGGAGAGCTGCCTTGATAAGACCTCTTGGGCACCC(SEQ ID NO: 1028)ncMOC_nm240.930.930.910.920.920.920.910.85TGGGGAAGTCGCTGCTGAGAACTCCGATGCCAAGCGCTGACCCAGCCTCG(SEQ ID NO: 1029)ncMOC_nm250.850.880.820.840.860.860.870.76TGAATGGATCCAGAGGCTCTGTGATGCAGAAATCTAGCTACAAGCCACCG(SEQ ID NO: 1030)ncMOC_nm260.910.890.890.910.930.910.910.86CGTAATGATCTTGAGGAAGAAAGAAAATGCAAAGGGAAGTATGAAATAGC(SEQ ID NO: 1031)ncMOC_nm270.860.890.890.890.890.900.900.89CGGTCTAATTAAAATAGGGAACAAGAACCAAAAAATCCCCTAGTTCCAGG(SEQ ID NO: 1032)ncMOC_nm280.830.840.800.810.820.830.840.79CGGTGGAGTTCGGAGCAATTTTTTGCAGGCAGGAAGTGGATCTTACAAAG(SEQ ID NO: 1033)ncMOC_nm290.850.870.750.810.810.810.830.72CGGGCCAAATCATCACTGGGCAGAACTAGGCCATAGGGTGCAAAATATAG(SEQ ID NO: 1034)ncMOC_nm300.920.850.850.860.890.870.870.73CGCCCCATAGGAAGTAGTAGAAGCGGCAGGCAGCTGTCCCCAGCGGCCAG(SEQ ID NO: 1035)ncMOC_nm310.910.920.910.920.930.930.910.87GGCCATAGTCACACCAACAGTCAAACAGGAATCGTCCCAGAGTGATGTCG(SEQ ID NO: 1036)ncMOC_nm320.890.870.870.870.860.890.870.80CGGCCTCCTTAGAATGTTTTAAGAATCGGCCATTAACTCCTGTGCTTGCT(SEQ ID NO: 1037)ncMOC_nm330.900.860.860.860.860.870.910.85CTCAGCTGTGGGGGCGTGTGCTGAGCACCAAGCAGAGGGAGCTGAGCCCG(SEQ ID NO: 1038)ncMOC_nm340.890.870.870.890.870.870.890.85GCCAAATGACTGTGTTGGCCTATGGGTGACCTGGCCCCTGGCTAGAATCG(SEQ ID NO: 1039)ncMOC_nm350.810.800.790.800.780.810.820.73CTGGATGGCAGACAGTGCGTGCAAGCATCACAGCCCACTGGAAGAGGCCG(SEQ ID NO: 1040)ncMOC_nm360.900.900.900.890.890.910.900.86TTCTTCAAAACCCTAGTCAGATATTGTTACTTCACTGAAAACTCTCACCG (SEQ ID NO: 1041)ncMOC_nm370.880.880.810.840.840.830.830.76TGGCTGATGTCTGCTGAACACCCGATCATTCACTCAACAGACAGCTCTCG(SEQ ID NO: 1042)ncMOC_nm380.890.930.950.950.960.960.960.95AGGTCAGCAGACGGTCACCGGGGAAAGCATCCAGGCATCTTGTCGCCTCG(SEQ ID NO: 1043)ncMOC_nm390.950.970.970.970.970.960.980.97CGAGGAGTTGCACTCTAGCTGCCGTGCCAGCAGTCTCGTCTGCTGTGAACG(SEQ ID NO: 1044)ncMOC_nm400.660.890.840.840.820.840.740.78CGGACTGACTGAACTTGACCTGTGACCTCTGACCCGGGGAGCAGAGAACA(SEQ ID NO: 1045)ncMOC_nm420.890.860.860.830.860.870.890.88CGTGCTGTAGAACATGCAAGACAGCACCCTGATGTGGGTGAATCTCATTT(SEQ ID NO: 1046)ncMOC_nm440.630.850.830.840.850.840.810.83GGTCGTGACCCTGCCTCCACCCTGTGTAAAGTCACAGCTGCAGGATCTCG(SEQ ID NO: 1047)ncMOC_nm460.820.800.780.770.790.770.830.77CTGACAAGGGCAGAGGCACAAGCAGGAGGGTGCAGCCTGTGGAAGGCCCG(SEQ ID NO: 1048)ncMOC_nm480.860.780.870.860.870.860.830.87GGGGATGCCGGCGACTCAGTAGTAAGGCAAGTCCTGCCACCTCCTGGCCG(SEQ ID NO: 1049)ncMOC_nm500.870.900.910.930.930.920.910.91CGGGGCACAGTTAACTTACCCCTTAGGACCAGGAAGTAATCTTTGTGGTA(SEQ ID NO: 1050)
TABLE 4GGranolucytes and Subtypes MarkerNon-Baso-Eosin-Neu-Clas-clas-philophiltrophilsicalsicalNKMarker-Granu-Granu-Granu-Mono-Mono-clas-IDTargetIDSYMBOLAccessionlocyteslocyteslocytescytescytessicalGRC_nm38cg15010903TIMP2NM_0032550.220.090.100.850.870.89GRC_nm39cg11014468DCP1ANM_0184030.060.090.090.930.910.91GRC_nm40cg07468327——0.090.070.120.760.820.87GRC_nm41cg21285555PCMTD1NM_0529370.180.080.050.780.800.78GRC_nm42cg08110693PXT1NM_1529900.060.010.200.720.770.88GRC_nm43cg13595556——0.110.060.040.680.770.87GRC_nm44cg03423077LOC339524NR_0269860.010.070.150.670.740.90GRC_nm45cg00121045UNKLNM_0230760.140.130.110.670.740.81GRC_nm46cg07305933PVT1NR_0033670.050.050.040.560.630.77GRC_nm47cg23661721——0.090.080.060.530.650.90GRC_nm48cg06168950——0.100.110.120.610.640.83GRC_nm49cg08435683SLC23A2NM_0051160.020.110.490.950.940.95GRC_nm50cg00335124PDE4DNM_0011658990.120.050.050.760.840.34GRC_nm51cg06526020NUDT3NM_0067030.310.060.050.800.830.90GRC_nm52cg03820688MTIF2NM_0024530.080.270.160.800.820.90GRC_nm53cg15034267GTPBP1NM_0042860.140.110.330.840.840.85GRC_nm54cg01400750ANAPC10NM_0148850.370.060.030.780.810.87GRC_nm55cg24419094RRM2NM_0010340.160.090.250.790.800.87GRC_nm56cg11313468HNRNPUL1NM_0070400.310.110.060.740.840.89GRC_nm57cg00705730NCK2NM_0035810.670.070.040.870.890.89GRC_nm58cg15609237TTNNM_1333780.480.090.160.790.870.95GRC_nm59cg19513582UBE2HNM_0033440.650.080.130.900.890.81GRC_nm60cg10687936ZNF148NM_0219640.050.120.580.840.860.90GRC_nm61cg18168663REC8NM_0010482050.060.100.260.730.740.71GRC_nm62cg26814100MAP7NM_0039800.130.120.280.730.820.92GRC_nm63cg10692528NCAPD2NM_0148650.080.160.610.860.890.87GRC_nm64cg05120113GLB1NM_0011356020.120.170.450.810.830.89GRC_nm65cg01799818VPS53NM_0182890.310.120.420.860.850.89GRC_nm66cg02722672GRK4NM_0010040570.550.060.250.820.900.93GRC_nm67cg06997767TRPS1NM_0141120.030.110.210.640.730.43GRC_nm68cg05575639CHD7NM_0177800.380.090.170.780.780.86GRC_nm69cg18502618COL18A1NM_1304440.620.110.210.880.850.90GRC_nm70cg05684528——0.070.080.160.630.710.77GRC_nm71cg11958668RNF103NM_0056670.270.140.650.890.910.81GRC_nm72cg14543285RCOR1NM_0151560.630.110.100.820.830.86GRC_nm73cg20836212VKORC1L1NM_1735170.060.180.640.820.860.89GRC_nm74cg25643253VKORC1L1NM_1735170.070.180.650.820.820.86GRC_nm75cg19282952——0.100.170.540.820.800.88GRC_nm76cg24559796——0.060.160.550.760.810.87GRC_nm77cg08864944PBX1NM_0025850.050.060.050.630.510.14GRC_nm78cg13416889ZNF609NM_0150420.170.200.670.860.880.84GRC_nm79cg21762728C6orf70NM_0183410.440.130.140.730.800.93GRC_nm80cg11596902——0.160.050.050.590.610.88GRC_nm81cg11231701CDK5RAP1NM_0160820.600.040.900.740.780.78GRC_nm82cg26647135PILRBNM_1750470.650.150.180.840.850.88GRC_nm83cg07268332AMPD3NM_0010253890.570.080.140.740.780.86GRC_nm84cg19935471MATN2NM_0305830.760.100.100.850.790.84GRC_nm85cg08505883——0.090.110.390.670.740.87bGRC_nm1cg02329886HDCNM_0021120.060.840.900.910.890.90bGRC_nm2cg26676468MCCNM_0023870.020.900.960.960.950.95bGRC_nm3cg01782059ERI3NM_0240660.030.750.970.960.960.97bGRC_nm4cg12646067TTLL8NM_0010804470.030.870.960.950.950.95bGRC_nm5cg05012676ZFPM1NM_1538130.040.880.960.960.950.95bGRC_nm6cg17306637TFB1M;NM_0160200.050.870.890.880.900.90CLDN20bGRC_nm7cg22197708MS4A2NM_0011423030.050.810.910.900.890.88bGRC_nm8cg03520003DENND3NM_0149570.090.810.900.920.910.90bGRC_nm9cg16643422DLC1NM_1826430.060.590.860.860.860.87bGRC_nm10cg18281744MAS1LNM_0529670.080.820.890.900.900.57bGRC_nm11cg07862744MAD1L1NM_0035500.160.920.930.910.920.93bGRC_nm12cg03555710PFKFB3NM_0011454430.080.810.960.970.970.97bGRC_nm13cg24057792——0.050.690.930.940.910.93bGRC_nm14cg26673070——0.050.840.920.920.920.92bGRC_nm15cg24130568TBCDNM_0059930.040.880.920.850.780.94bGRC_nm16cg04498104PFKFB4NM_0045670.060.800.910.900.910.84bGRC_nm17cg12037509DPYSL2NM_0013860.070.840.920.930.910.93bGRC_nm18cg11294011——0.080.920.940.930.930.91bGRC_nm19cg02752529FBXL14NM_1524410.040.710.890.900.900.89bGRC_nm20cg02426739SGSWAPNM_004592;0.050.750.910.920.910.61NM_001261411bGRC_nm21cg12087639ADKNM_0011230.090.890.950.920.920.91bGRC_nm22cg10319857NFAT5NM_1387140.040.600.910.910.880.90bGRC_nm23cg21715896——0.060.780.880.900.870.90bGRC_nm24cg14200678MEGF9NM_0010804970.080.820.910.890.890.90bGRC_nm25cg20964248SIK2NM_0151910.040.800.900.850.850.89bGRC_nm26cg03380342——0.070.850.910.910.900.90bGRC_nm27cg07818422WDFY2NM_0529500.050.640.920.920.910.90bGRC_nm28cg23639055——0.070.840.900.900.900.89bGRC_nm29cg00086283——0.110.880.940.950.940.94bGRC_nm30cg12018521TESNM_0156410.060.840.900.900.880.65bGRC_nm31cg12486498C1orf198NM_0011364940.120.880.940.930.930.95bGRC_nm32cg19699264SDPRNM_0046570.070.880.920.900.910.92bGRC_nm33cg05865769MAP2K4NM_0030100.080.750.910.920.890.90bGRC_nm34cg11809342TANC1NM_0333940.080.760.910.920.910.89bGRC_nm35cg02800334ANXA13NM_0010039540.050.800.880.880.860.87bGRC_nm36cg09151061ZNF366NM_1526250.090.900.920.920.910.90bGRC_nm37cg14633252SHBNM_0030280.050.780.890.810.800.90bGRC_nm38cg09473249ABCC1NM_0198620.070.730.880.900.890.90bGRC_nm39cg19975917LPPNM_0055780.070.630.900.910.900.89bGRC_nm40cg02387491LIN7A;NM_0046640.080.630.920.910.910.90MIR617bGRC_nm41cg24143196TECRNM_1385010.080.660.910.930.930.78bGRC_nm42cg22609618CDC14ANM_0036720.070.880.870.910.880.88bGRC_nm43cg24791846——0.090.850.910.890.890.92bGRC_nm44cg10330847——0.060.650.900.910.890.73bGRC_nm45cg04988216ROR1NM_0050120.130.900.910.940.940.92bGRC_nm46cg26009797——0.060.780.860.890.870.87bGRC_nm47cg24736010——0.080.820.910.910.910.89bGRC_nm48cg04657468ARID5BNM_0321990.090.700.880.910.870.89bGRC_nm49cg04023434RGL1NM_0151490.100.690.920.900.930.90bGRC_nm50cg15192986CPB2NM_0164130.090.820.880.890.870.90eGRC_nm2cg15090899RPS6KA2NM_0010069320.970.160.830.950.960.78eGRC_nm3cg20761853TIMP2NM_0032550.740.130.610.930.940.91eGRC_nm4cg11900509ANXA11NM_1458680.920.130.620.980.980.97eGRC_nm5cg03269757ATL2NM_0223740.520.140.780.880.870.93eGRC_nm6cg09411597C10orf18NM_0177820.820.130.610.870.860.88eGRC_nm7cg13872812BBXNM_0202350.810.220.950.950.950.96eGRC_nm8cg21237481——0.800.170.760.870.870.93eGRC_nm9cg23060513FARSANM_0044610.850.180.540.830.890.93eGRC_nm10cg08742095CALUNM_0012190.810.150.570.890.920.88eGRC_nm11cg22011526C6orf89NM_1527340.880.160.590.850.860.90eGRC_nm12cg24520381PPP1R1BNM_1815050.850.160.730.860.890.90eGRC_nm13cg10454864——0.540.210.930.940.930.92eGRC_nm14cg10387956HEXANM_0005200.620.140.810.840.840.85eGRC_nm15cg18898103ETS1NM_0011438200.860.160.530.870.840.89eGRC_nm16cg00006459——0.780.190.870.900.890.89eGRC_nm17cg20240243MEF2ANM_0011309270.680.180.910.870.850.87eGRC_nm18cg23990557IGF1RNM_0008750.860.170.590.860.900.88eGRC_nm19cg19788934C12orf43NM_0228950.790.180.700.860.840.86eGRC_nm20cg11668148HEXANM_0005200.870.190.870.890.860.87eGRC_nm21cg16386158IL1RL1NM_0162320.560.180.830.910.920.74eGRC_nm22cg26234644TMEM220NM_0010043130.690.180.700.750.730.91eGRC_nm23cg25381747——0.710.180.850.860.830.86eGRC_nm24cg22221575PCYT1ANM_0050170.570.160.820.820.810.85eGRC_nm25cg11310939MARCH3NM_1784500.600.210.890.910.880.89eGRC_nm26cg09596645——0.820.200.850.830.840.86eGRC_nm27cg00391067LOC100-NM_0011454510.700.170.720.760.770.88271715eGRC_nm28cg01835368C7orf36NM_0201920.740.150.580.710.730.80eGRC_nm29cg16797699——0.740.160.660.740.760.74eGRC_nm30cg13953978USP20NM_0011103030.610.200.830.860.850.83eGRC_nm31cg17572056OSTalphaNM_1526720.980.110.270.950.980.98eGRC_nm32cg04836151——0.980.150.490.840.860.98eGRC_nm33cg02803925PCYT1ANM_0050170.970.210.950.990.990.98eGRC_nm34cg00421164RREB1NM_0010037000.870.120.390.860.870.91eGRC_nm35cg03695871DKFZp7-NM_1383680.890.170.510.840.910.9361E198eGRC_nm36cg26921611EIF4EBP1NM_0040950.770.100.470.710.790.88eGRC_nm37cg15171342TMED3NM_0073640.820.210.770.930.920.92eGRC_nm38cg05736642HTTNM_0021110.890.220.820.920.920.92eGRC_nm39cg23039807——0.860.140.450.730.790.90eGRC_nm40cg04128967——0.410.120.830.790.820.90eGRC_nm41cg11183227MAN2A2NM_0061220.980.270.750.980.980.98eGRC_nm42cg23037469DCAF5NM_0038610.890.160.440.860.870.89eGRC_nm43cg25578728CHD7NM_0177800.850.200.780.910.890.92eGRC_nm44cg12910830MAT2BNM_1827960.730.210.870.910.900.91eGRC_nm45cg08077807PRKCHNM_0062550.740.200.920.920.930.82eGRC_nm46cg14209186TMEM156NM_0249430.750.210.760.800.870.92eGRC_nm47cg05078091APLP2NR_0245160.580.230.920.930.930.92eGRC_nm48cg19764973STX3NM_0041770.870.240.870.910.900.91eGRC_nm49cg25203627TSNAX-NR_0283940.890.250.800.890.910.92DISC1eGRC_nm50cg22106847DMXL1NM_0055090.890.260.820.900.910.90eGRC_nm51cg17960717——0.900.280.870.920.890.93nGRC_nm1cg03146219NADSYN1NM_0181610.980.880.070.970.980.97nGRC_nm3cg13785123ENO1NM_0014280.950.780.040.880.920.96nGRC_nm4cg23819411MCF2L2NM_0150780.950.690.030.780.860.96GRC_18nmcg25600606HIPK3NM_0010482000.910.770.040.870.870.92nGRC_nm7cg25074794MARCH8NM_0010022650.900.560.040.830.900.95nGRC_nm8cg13618969FAM125BNM_0334460.880.760.030.890.910.90nGRC_nm9cg26056277——0.930.680.050.800.840.96nGRC_nm10cg11153071RPTORNM_0011630340.970.850.060.600.770.97nGRC_nm11cg01498832RPTORNM_0011630340.860.760.120.610.700.86nGRC_nm12cg21090866VPS53NM_0182890.910.870.070.920.930.88nGRC_nm13cg05971678CHST15NM_0158920.930.660.040.610.730.97nGRC_nm15cg09694051MED21NM_0042640.870.750.010.800.840.88nGRC_nm16cg24131359CPMNM_0018740.960.910.130.940.980.96nGRC_nm17cg13984928ITGAENM_0022080.970.750.040.580.610.85nGRC_nm20cg13468144ANKFY1NM_0163760.900.720.040.900.910.91nGRC_nm22cg01699630ARG1NM_0000450.910.740.050.900.880.87nGRC_nm24cg10934870PCYOX1NM_0162970.900.850.050.850.900.89nGRC_nm25cg26396370KLF11NM_0035970.830.750.050.810.830.91nGRC_nm26cg25693317SH3PXD2BNM_0010179950.900.750.080.840.890.91nGRC_nm28cg12031275——0.950.770.110.760.810.95nGRC_nm29cg23128584DIP2CNM_0149740.850.510.050.660.810.91nGRC_nm30cg02279108——0.870.740.060.890.900.88nGRC_nm31cg25757820——0.920.760.080.740.760.90nGRC_nm32cg06465076CASTNM_0017500.760.590.070.760.830.91nGRC_nm33cg27510066CSGALNACT1NR_0240400.870.670.060.790.830.89nGRC_nm34cg06784232CSGALNACT1NR_0240400.830.790.240.830.860.84nGRC_nm35cg01040749INPP5ANM_0055390.850.510.080.820.860.91nGRC_nm36cg07102397FOXN3NM_0051970.880.720.100.860.860.92nGRC_nm37cg13633625——0.820.670.050.640.670.92nGRC_nm38cg23338668——0.870.830.070.870.860.88nGRC_nm39cg22400420RGL1NM_0151490.870.780.070.840.880.84nGRC_nm40cg24737761——0.860.540.060.810.830.85nGRC_nm41cg23911433——0.870.810.050.780.870.85nGRC_nm42cg09010699——0.870.790.070.670.690.89nGRC_nm43cg06633438MLLT1NM_0059340.920.790.090.730.800.90nGRC_nm44cg16000989DCAF4L1NM_0010299550.940.730.110.670.760.94nGRC_nm45cg03610527HDLBPNM_2033460.840.570.100.700.720.93nGRC_nm46cg17419815C12orf71NM_0010804060.890.670.070.610.650.91nGRC_nm47cg06059360NKTRNM_0053850.750.710.090.740.780.87nGRC_nm48cg07052231PEX5NM_0011310230.860.730.090.700.810.87nGRC_nm49cg02368812NQO2NM_0009040.960.790.190.800.830.97nGRC_nm50cg05418105——0.880.660.080.580.620.91CD4+ThCD4+Cen-CD4+ ThCD8+Marker-B-ThCD4+CD4+tralEffect.CytotoxicNKIDCellsnaiveTh1Th2Mem.Mem.T-CellsT-CellsDiscovery FragmentGRC_nm380.870.900.860.870.880.870.890.86CGGCCTGGGCGTGGTCTTGCAAAATGCTTCCAAAGCCACCTTAGCCTGTT (SEQ ID NO: 1051)GRC_nm390.910.900.910.920.920.910.920.92CCACAGACCCTTTCTCCTTCACTGATTACAGAATCATACCAAGCACAGCG (SEQ ID NO: 1052)GRC_nm400.870.920.870.890.880.870.890.85TGGGCCTGGTGCTTGGGTTTGCTAACTTCTGGTTCTTCATGTGTATCACG (SEQ ID NO: 1053)GRC_nm410.870.890.860.870.880.870.890.84CGACATGGGCAATGTGGGGAAAGAGACCATTGTGTAAATGATCTACAATG (SEQ ID NO:1054)GRC_nm420.870.890.860.870.890.890.910.85CGAAGGCCAGAGCCTGTTTGTAAACCATTAACAGGAATAACAAGAGATAA (SEQ ID NO:1055)GRC_nm430.910.910.860.890.890.880.910.84GACCGAGGCCGACAATTCAGTCGCCACACAAGAGGTCAGAAATATACTCG (SEQ ID NO:1056)GRC_nm440.910.920.900.910.910.900.890.88TGGGGATAAACGGTGTAACACTGGGGCAGGTCAGTTTCCTTGTTGGTACG (SEQ ID NO:1057)GRC_nm450.850.930.750.830.870.840.850.73TTTGAGGAAAATACCTTGAAACCGTCGGTAGGACTAGATAGGTGACAACG (SEQ ID NO:1058)GRC_nm460.740.860.670.680.760.730.780.70CGTCTTGGTGATAACAGGCACTTGAGAAATAAGTTTTTAAAGAGTTGATT (SEQ ID NO: 1059)GRC_nm470.890.870.890.890.900.890.880.90AACACAGTGTGGGCTGATGCAATCAGTGTTTGCTGCCCTTGGGCGCTTCG (SEQ ID NO: 1060)GRC_nm480.870.900.850.850.850.840.870.82CGGGCAGATTTTTTCAGAGCAATTGAATGTATTCAAAGATGTCTTAATTA (SEQ ID NO: 1061)GRC_nm490.960.940.960.960.960.970.960.95GAAGCTGGGGCAGGTAACACGCAGAGCCGCCACGTGGAACGGTCTGTCCG (SEQ ID NO:1062)GRC_nm500.910.670.690.660.700.710.650.61GGAGGCACTTGTAGCTGAGTGAGGGCATTTCCTTTGTGCAGTGGTATGCG (SEQ ID NO: 1063)GRC_nm510.900.890.910.890.900.890.900.88TTCTTGTTATCTCATTTAGGACTCATAACTCAGTTGTGTAAGCTTTATCG (SEQ ID NO: 1064)GRC_nm520.890.880.870.840.860.870.880.87CTATCACTAGACATATCCTCTCTTTAGAGAAATCACACAAAATTCTACG (SEQ ID NO: 1065)GRC_nm530.870.870.840.840.840.870.890.81AGGATTTGCTCTCCAGATGCAGCTGTGCCTTCCTTTGAAATATCTTTCG (SEQ ID NO: 1066)GRC_nm540.860.550.830.850.790.870.740.87TCTTGAGAAATGTACTTTAGACTAGCTTGAGTTGACACATTACAAAGTCG (SEQ ID NO: 1067)GRC_nm550.870.840.840.810.880.790.830.85CGGTATCAGCAATTGAAGCATTACAGTAAAAGACCTCCGATTACCAACTG (SEQ ID NO: 1068)GRC_nm560.870.890.850.850.860.860.880.79CGGCCCCTTCTGACCCCATAGCTGGCACGGGCTCCTGACCACAGGTATGC (SEQ ID NO: 1069)GRC_nm570.890.910.900.850.900.890.890.90TGCCCCGGTGGTGCAGTCAGTGGAAGCAGCTGTAATCTATGGGGTCATCG (SEQ ID NO: 1070)GRC_nm580.660.970.960.960.970.940.980.96CGGTGTCACAAGAAAACCTTGCAGACTCGCCCTCGTAGACGGTCATGGAC (SEQ ID NO: 1071)GRC_nm590.940.870.850.820.870.870.790.77CGTGGTACATGAGAACCTTACTATAAAGTGGCTCTTTAGGACCGTTCTGA (SEQ ID NO: 1072)GRC_nm600.920.920.880.850.900.890.920.91CATGAACTCTCTGCGTTCCAAACTATAGATTGTGATTAATTATTTTGTCG (SEQ ID NO: 1073)GRC_nm610.840.770.560.600.660.630.730.38GCACCCCAGTTATCTAGCCCTCATCAATTTGTGCAAGAAGGCCGGGCTCG (SEQ ID NO: 1074)GRC_nm620.920.900.910.920.920.920.920.92CGCAAGTGATTTATAGGCATTGTCTTTGCAGCCACTCTATGAGGCAGACA (SEQ ID NO: 1075)GRC_nm630.900.920.860.810.850.870.890.88CCACTCTGACCTTAGACAAGTTACTTAATTGTCTCAGTGCCTTGGTTTCG (SEQ ID NO: 1076)GRC_nm640.890.930.860.790.870.810.900.87ATTTCATCAACTGTCCCACTAACATCCTGTATATACCAAGCTTCTTATCG (SEQ ID NO: 1077)GRC_nm650.900.900.870.860.890.890.910.87CGCTTTGGAAGAAGGATTAGGTAATTGTAGTACAATCTTCCACCCAGTTC (SEQ ID NO: 1078)GRC_nm660.950.950.950.950.950.950.960.93CGGACCTCAAGTCCCTGTGCTAGCCACGGTAGTTCTTCACACCCCGTCAC (SEQ ID NO: 1079)GRC_nm670.760.930.560.880.750.660.820.61ATGGCGGATATGTATGCAACGCGTGTGGCCTCTACCAGAAGCTTCACTCG (SEQ ID NO: 1080)GRC_nm680.520.730.900.880.850.880.890.91AGGTAGCCATGCTGCTAAGGTCACAGTCACTAAGATATTTTTTGTCATCG (SEQ ID NO: 1081)GRC_nm690.970.970.970.960.980.970.970.97GGTTACGGGGCAGTGGCCATGAGCCTCTGTCGGACTGACGCAAGGAGCCG (SEQ ID NO:1082)GRC_nm700.770.860.550.610.700.600.700.34AAAAAATAGACAACCTCCCAGTTGCCACAGACATGTACTGTAAGCAGACG (SEQ ID NO: 1083)GRC_nm710.920.890.880.860.880.860.910.87CGGGAAATACACATTATGCTAATGTTGATGACAGAATTTATTTGGTTGCC (SEQ ID NO: 1084)GRC_nm720.870.860.860.840.860.870.880.80CGGTGCCATCTTGTGAAAAGGGCTCTGCAGCTTTTAATGTGTACAGTTTC (SEQ ID NO: 1085)GRC_nm730.900.910.900.890.900.900.910.88GGCCTACATTCTGTACTTTGTGCTGAAGGAGTTCTGCATCATCTGCATCG (SEQ ID NO: 1086)GRC_nm740.860.870.850.850.870.860.880.86CGTGACGATGCAGATGATGCAGAACTCCTTCAGCACAAAGTACAGAATGT (SEQ ID NO:1087)GRC_nm750.690.880.900.910.920.920.920.89CGCCAGCCTGCATTTTAGATGGACCATAACTCAAGATAGGCGTTGAAGCA (SEQ ID NO:1088)GRC_nm760.860.890.840.850.860.860.860.79CGAGGGCACTGGACATGCTGGATTTGGGGAGACTGTTATGCGATCTCAAA (SEQ ID NO: 1089)GRC_nm770.760.850.750.760.740.740.770.58CAGAGGAAGCCACATAACCTCAAAAGGTCAAGACACCTAGACATGGTCCG (SEQ ID NO:1090)GRC_nm780.900.890.900.890.880.870.890.86CAACCTGTCCACTCGGTTTTCTGTTTCTTTGAGATTATTTTCTACTAACG (SEQ ID NO: 1091)GRC_nm790.920.900.920.930.910.940.930.93CGGTGTGATGTGATGAAATCAGGATTTTGTGTAAGCTAGCTCTCAAGAAA (SEQ ID NO: 1092)GRC_nm800.910.900.510.590.620.560.800.47ATCCTGCTTCCATGGAGTAAAATTCCAGACTGGGACAAGCGTTCTTTCCG (SEQ ID NO: 1093)GRC_nm810.780.800.710.760.750.770.820.68CGTGTCTCTTTAAAGCTGCTATGTGAACAGCTTTTACAGTCATTAAATTT (SEQ ID NO: 1094)GRC_nm820.880.890.890.890.900.900.900.87TGTATGTCCAGCTGGACTTGGCAGAAGTACACAGACTGGTCCTCCTTCCG (SEQ ID NO: 1095)GRC_nm830.500.810.820.800.820.820.850.80GACACATGATCCTCGGGCTGCTGCTGGGCTTTAGCTACCCAGAGATTACG (SEQ ID NO: 1096)GRC_nm840.800.840.860.850.830.870.870.86ATTTCCTATGGCCAGTGTTCTACAGAAGTAAGACTGTGCAAACTTTATCG (SEQ ID NO: 1097)GRC_nm850.900.900.850.870.880.850.900.88GGCTTCTGACTGGAGGACAATGACCCAGCTGATCCTTCTGACGTCTTACG (SEQ ID NO: 1098)bGRC_nm10.910.910.910.910.900.910.910.89AAGAAAGAACCCTTTAAATAAAGGGCCCACACTGGCTGCCAGG GAGTGCG (SEQ ID NO:1099)bGRC_nm20.960.950.970.960.960.960.940.95CGGGGGGCCACCGAATACTCCCCGAGCGCATACTATTTACAGAAGAGTCA (SEQ ID NO:1100)bGRC_nm30.960.960.960.970.970.970.970.97GACGTGCAGATAACGTTGAGCTGCCCTGTCCCCGAGCCATAAGCAGAGCG (SEQ ID NO:1101)bGRC_nm40.960.950.960.950.960.940.950.96CGGTCACTTCCAGGTTTTGACGATCATGAATAACGTTTCTGTCGACATCT (SEQ ID NO: 1102)bGRC_nm50.960.960.960.960.950.960.960.96CGCCTATCGGCCCATCTCCCTGCTGTCCATCAGGCCGGGCCCCCGCCTCA (SEQ ID NO: 1103)bGRC_nm60.920.890.890.890.890.910.910.90CGTCCTAGACACCCTGGCCTGGAAACTAGGACATCTGCCTCGGGCCTGTT (SEQ ID NO: 1104)bGRC_nm70.890.900.860.870.880.870.880.85CGCTGCAGCAGATGGTCTTGGAAATACAACAGGCTGCATTCTAACTGCTG (SEQ ID NO: 1105)bGRC_nm80.910.910.910.920.900.910.920.92ATAACTTGGAGGCAGCGTAGATGGCGCCTGGTGACTGCAGTGTGCCCACG (SEQ ID NO:1106)bGRC_nm90.850.890.760.780.810.800.840.71CGTCAGGGCTGTGGTGATGAAGTCCAGATGTTATAACTTAACAGTGTTTT (SEQ ID NO: 1107)bGRC_nm100.860.910.850.850.870.860.880.82GGCCTGCTGTCCCACTGCCATGCTCATCTGCATATGTATGGTTTCATTCG (SEQ ID NO: 1108)bGRC_nm110.930.920.920.930.920.930.930.93CGCTAATGCCAAGATAAGCTAATGCTGTGCTTCACCTGGACACAGGGAAA (SEQ ID NO:1109)bGRC_nm120.980.970.960.960.960.960.970.96TCACCTGCGGAGGACCCCGTGCTGGGGAGGTGGTGGCTGGTAGTGAGACG (SEQ ID NO:1110)bGRC_nm130.930.930.940.930.930.910.940.94CGAAGGCTTTGTAATTCACAGTGATAAGTGCAGTTAATATGTTATCTGAT (SEQ ID NO: 1111)bGRC_nm140.910.920.920.910.910.910.920.93ACTGCCCATTTTTTAAAACTTCAAATCCAAAAGATGTGATAAATAGTACG (SEQ ID NO:1112)bGRC_nm150.760.920.930.950.950.940.920.93CTCTCGGGAAGACAGGGCTGCTGTGTATCCTGATTGTGGTGGTGGATACG (SEQ ID NO: 1113)bGRC_nm160.930.940.940.920.930.930.950.91GAGGGGACAGTCCTGGGTCCCCGCCAATCCGGCCCTTGAGGTTGAGCTCG (SEQ ID NO: 1114)bGRC_nm170.920.920.920.930.920.930.900.93ATAGGTGAATTCTATAGCCAGGTGGCCTCCAGAAGCTTACGAAATGATCG (SEQ ID NO:1115)bGRC_nm180.930.930.940.930.940.930.930.93CGCCCTGCGTTGCGTTCTCCACACAGCAGCCACGGTGACTTTGTTAAAAT (SEQ ID NO: 1116)bGRC_nm190.890.910.890.880.910.870.900.88CGGAATATTCAAAACCAGATGGACAGTTAGGTCGATAGATAAGACAGATA (SEQ ID NO:1117)bGRC_nm200.840.950.960.950.970.950.940.94AGTGCGCTGCTGCGGGAGGAAGCCAGTGTCTTCCTGGAGACGGCTTCACG (SEQ ID NO:1118)bGRC_nm210.930.920.920.920.930.930.930.90CGCTTTGAGATTGAAGAGAACATACACTGGACCATATAGGGGTCTTCTAC (SEQ ID NO: 1119)bGRC_nm220.890.900.900.890.900.900.910.87CGGCTTCCTTTGATGGGAGACAGGAGGAGTAGAAATAAGCTGAGCTACAC (SEQ ID NO:1120)bGRC_nm230.910.910.890.880.900.910.900.91ACTGAGCAGCAAGTATTCCTTGTGTACCAGTCTCTGTTCCAGAAACAACG (SEQ ID NO: 1121)bGRC_nm240.900.900.910.910.940.910.930.91CGGAGAAATGCAAATCTGATAATAAGCACATATATAGATGGCATTTAAAT (SEQ ID NO: 1122)bGRC_nm250.880.890.870.890.890.870.860.89GCTTTATCTAACAATTTATTTAACAAACAGTTAACTAGCACTGTGTGCCG (SEQ ID NO: 1123)bGRC_nm260.890.900.910.890.910.900.920.90CGGAACCCTGACTTTGGAGGCTTCAGACATCCTGAAATATAATTCAGATA (SEQ ID NO: 1124)bGRC_nm270.910.910.860.870.880.890.910.89CCTGGTCACAACATTCAGAGGACACACAGGTAGGATTAACAGTAAAATCG (SEQ ID NO:1125)bGRC_nm280.880.890.910.890.900.890.920.87GCCAGGATCACAAAGTTTCTGCCTTATCATTTATGGTTATTGTTACCTCG (SEQ ID NO: 1126)bGRC_nm290.930.940.940.940.940.940.940.95AATAAGAAGAGTCCGTACCTCTTTCCCCTCACTCTGCACCCAGAATACCG (SEQ ID NO: 1127)bGRC_nm300.900.920.910.910.920.910.910.89TTCAGCAGATGAGATCTCAGCAATCCCCACTAGGCTGGCTTCTAATAACG (SEQ ID NO: 1128)bGRC_nm310.950.950.940.930.940.960.960.95TGGCTTCTGCCAGAGAAGCCCCGGACAGCTGCGAGCGCTGGCTGAGAACG (SEQ ID NO:1129)bGRC_nm320.900.910.860.880.900.860.900.82GGCAGGTCTTCTGACTTGGTCTCATTTTCTGCATGGCTTTCTCCCTCTCG (SEQ ID NO: 1130)bGRC_nm330.900.900.890.900.920.930.900.91CGTGGCTTTTGATTATCTGCAAAGATTAATGAGCCCTAATGAACGGGTCA (SEQ ID NO:1131)bGRC_nm340.910.920.880.880.900.900.920.90GTCCCACTGGGGCACACAGCAGAGCAATGAAATTCCTGCATATTAAGACG (SEQ ID NO:1132)bGRC_nm350.880.900.850.840.880.850.830.84CGGTAGACTGATGAAATAAGGTTTGGTTCATATCCATAACAGTTGACTAC (SEQ ID NO: 1133)bGRC_nm360.890.930.900.910.900.910.890.87CGGTAGGTGTGCACAAGCCAGAGCAGAGTCCCATTCCTTGCATCCGCCAC (SEQ ID NO:1134)bGRC_nm370.900.920.880.880.900.880.840.83CCTGGCACCTGCTTCACAGCCTTCCCGCTTGCCTGCTTTGTGGTGAGTCG (SEQ ID NO: 1135)bGRC_nm380.900.900.890.900.880.910.910.89CGGTCTGATCTGAACTCGGCTTCAGTTGGTCTGGAATGCACCGGCTGCAT (SEQ ID NO: 1136)bGRC_nm390.910.910.900.860.900.900.910.91CGCTGAATCATGGAGTTTATCTTAAGGATGGATCTGAATGAGATCTGATA (SEQ ID NO: 1137)bGRC_nm400.920.910.890.910.900.910.910.87AAATTCTGAATTTTCGCTACACTG TCCACAGTACCAAATGGCAATAACCG (SEQ ID NO: 1138)bGRC_nm410.920.920.890.870.910.910.930.91CGGTGGCTGTTTCCATAGTAGCCTCATATCACTGCCAAATCTCATCTGAT (SEQ ID NO: 1139)bGRC_nm420.790.890.860.850.870.870.860.88CTATCTGTGACAGATAACCTATATCACAGATAGATCTATCTGTGACCTCG (SEQ ID NO: 1140)bGRC_nm430.900.900.880.910.910.900.890.88CGCAATAAGCACAGAGCTGGACTTGAACCCAAGTTTTGCCACACAGGCCT (SEQ ID NO: 1141)bGRC_nm440.890.890.900.890.890.890.900.90GGCTCTGTGGGTTTGGCTCTTAGAGTCAAGATGGTCACCGCCTCCAAGCG (SEQ ID NO: 1142)bGRC_nm450.920.930.910.930.930.940.940.93CACTAATTACCACTCAGTTCTTGGGCTGTAGCAAAGATAATTTCAATTCG (SEQ ID NO: 1143)bGRC_nm460.880.880.850.740.850.840.890.86CGCAGTTATCTGTGGCTGATCATGGCTTGTCATACTGCTACTCCTAGATG (SEQ ID NO: 1144)bGRC_nm470.900.910.820.830.860.850.890.85CGCTGGTGTGGGACCAGTCTCCTAGACCCAAGTGCTAGGAGTAGAATGCT (SEQ ID NO:1145)bGRC_nm480.890.910.890.920.910.910.890.86GCATCCTAACAAATGAACAATCTTTAGCTAAAGACACTGACCAGATTACG (SEQ ID NO:1146)bGRC_nm490.890.910.910.910.910.920.910.89CGTATGAGGTTATGTAGCATGTGAGGATAGGCATAGCTTTGTTACGTGTC (SEQ ID NO: 1147)bGRC_nm500.870.870.870.880.880.880.900.91CGCTGATAAATCTCTTGAGTTTTTCAAGAAGGTGACAGTGTATACCATGA (SEQ ID NO: 1148)eGRC_nm20.970.970.970.960.970.970.970.98CGCGGTGACACCTACAGCCACGCAAGCACCTGCGTAAACACGTGCTACAG (SEQ ID NO:1149)eGRC_nm30.930.920.910.900.920.900.920.86CGGCAACCCCAAAGCACCTGTTAAGACTCCTGACCCCCAAGTGGCATGCA (SEQ ID NO:1150)eGRC_nm40.840.610.940.920.880.960.720.98CCATGGAGGAGCGTGACGGAGAGATCTGCGTGTGACGCTGTGTGCTCTCG (SEQ ID NO:1151)eGRC_nm50.920.920.920.920.910.920.920.93CCCTATAATATCTTTACTGTAAGGCAGCTACTTCTCCCTAAATAATTTCG (SEQ ID NO: 1152)eGRC_nm60.740.910.900.880.890.900.880.90TAAAAAATTTCTTGCCACATACGAGTTTAAACCAAGATAATCACGGCACG (SEQ ID NO: 1153)eGRC_nm70.960.970.950.940.950.940.960.95CGCTATAGCAGTTTTTAAAAGCTTCTTCGATTGTTGACCGGTCCGTTAAG (SEQ ID NO: 1154)eGRC_nm80.920.930.920.910.930.930.930.93CGGAAGCCAAGCTCTGTCCCAAGCACTGTGCTGATGATATCTCATTTCAT (SEQ ID NO: 1155)eGRC_nm90.970.940.950.940.950.940.950.96CGCCGCTGCACCTCATCCTCCATGCTGTCCACCTGCCAGGATAAGGAGTG (SEQ ID NO: 1156)eGRC_nm100.910.910.870.850.870.870.880.87CGTGGAAGAGGGACAGAATTTTAGAGAGAGAAACTCATTTGAGAAATGGG (SEQ ID NO:1157)eGRC_nm110.890.910.890.900.910.890.910.89CGTCGTTATTCTTAGGAGATGCATGTTGAAATATTTAGAAATGATTTTAT (SEQ ID NO: 1158)eGRC_nm120.870.890.840.880.890.870.880.84ACAGGGACCTAATTAACTGACAGTTGGTCTGATTGCCAAGCTGAGGGGCG (SEQ ID NO:1159)eGRC_nm130.940.940.940.930.920.930.930.93CGAAACACAGTCATTCATGTTGGTAATTGTGACAGAGATTATGTGGCCCA (SEQ ID NO: 1160)eGRC_nm140.890.890.850.860.870.860.850.82AGATGGATAGTGGCTTCCTAATATCCCCTTTTCATCAGTGTTAAAAATCG (SEQ ID NO: 1161)eGRC_nm150.880.890.870.890.880.890.890.88TGAGGTTAAGAAATTTGCTCATGGCCATACACGCAGCAAGCAGTTCTACG (SEQ ID NO: 1162)eGRC_nm160.900.930.870.860.890.890.910.87CGGTTGCTTAAGCTGACACTGCAGAGCATTGCAAGAAGTGTTGATTAAAA (SEQ ID NO: 1163)eGRC_nm170.850.900.900.880.880.880.900.91ATTTGTATTTTGACAGCCCATGGTAGCATCAGATAAATTGCCTTTTAACG (SEQ ID NO: 1164)eGRC_nm180.890.890.850.860.870.870.880.85CGCACAACTGCTCCATCTTTTAAGATATTGGAAGTGAGAGCACGGGAGGA (SEQ ID NO: 1165)eGRC_nm190.860.890.860.860.870.870.880.87CTCCACAATAAGCTAAAGCCAACTCCTGCAACAGGCTCCTGTGATCAACG (SEQ ID NO: 1166)eGRC_nm200.890.870.850.830.870.850.870.81CGGTGCCTGGGGCTCAGGTCTGTTCAAACTCCTGCTCACAGAAGCCTACA (SEQ ID NO: 1167)eGRC_nm210.890.910.870.850.890.880.880.85CGCAATCCTCAGAAGCTGACAGGAGCTTCAGAGAGGAGAATTACCTTACC (SEQ ID NO:1168)eGRC_nm220.850.910.910.920.920.930.930.91ATTTACACATCCAIAGGCCTCATTTCTGCTGTTCTAAAGAGTCTTTATCG (SEQ ID NO: 1169)eGRC_nm230.870.870.850.850.860.860.860.84AACTCCTAAGGCCAAAGGAATGTGGTATGCTCACTGACTTGGCTTGGACG (SEQ ID NO: 1170)eGRC_nm240.790.840.820.810.810.810.830.79GGGGTAAATGGATGCAGAGCAGGCTTCTAAGGTGCAGTCCCCCTCCTTCG (SEQ ID NO:1171)eGRC_nm250.900.900.800.790.880.850.840.77CCAGGTGCAACATATGCATGCCAGTTGGTGCATGCAGCTTGTGAGGTCCG (SEQ ID NO: 1172)eGRC_nm260.840.860.780.810.820.780.830.78CGGGCAGTCTGTGGTTCCTGACCAGACTGCTGGGGGTCAAATCTCTTTCA (SEQ ID NO: 1173)eGRC_nm270.830.910.740.790.820.810.820.75GAATTTCCTAATATATTTCTAACAGATAATGGTCACCACCACTACCCTCG (SEQ ID NO: 1174)eGRC_nm280.860.880.780.750.770.770.810.67CGATTGTTAGGAAACCAAATGTTCTGAACATTATTTTCATTAGAAAAGGG (SEQ ID NO: 1175)eGRC_nm290.750.820.680.710.800.780.810.66AGCGGGAGGCTGGTGGCGTGCATCAGGCCATGGGGGTGGGGCTTGGACCG (SEQ ID NO:1176)eGRC_nm300.870.640.720.700.730.780.680.77CGACTGCTCAAACTGGGTTTGGAGAACAACCCAGTATGGCTTTTACAGAG (SEQ ID NO: 1177)eGRC_nm310.980.960.980.980.980.980.980.98CGGGATAAAGCACAGCTCCTCCGCCAGCCCGGCGCGCAGCGGGCCTCACC (SEQ ID NO:1178)eGRC_nm320.980.980.990.990.990.990.990.98CGCACTCCGGTGACTCAGAATTGTCGCCGCTCCGTGCAAGTAAGTGTTTG (SEQ ID NO: 1179)eGRC_nm330.980.990.960.990.980.980.990.96GGTGATGAACGAGAATGAGCGCTATGACGCAGTCCAGCACTGCCGCTACG (SEQ ID NO:1180)eGRC_nm340.900.910.920.920.910.910.910.93AGTATCTAGAAAAACCCAGAGAATGATATTCCACAAAACGGTAAGCATCG (SEQ ID NO:1181)eGRC_nm350.940.920.930.930.920.940.950.92CGCGGGAGCTGCGGGCTGCGGTGATCCAGCTTCTGGACACCTCCTATCTG (SEQ ID NO: 1182)eGRC_nm360.910.900.870.850.870.860.890.84CGCCCTAGGGCCAAGAGTTGGGCCCCGTCTGAGCTTTTTTCAACTCTGTT (SEQ ID NO: 1183)eGRC_nm370.930.930.920.930.930.930.930.92CCCAATAGAGGCTGTCTCAACAGTGGCCAACAGAACTCTCATGAGTATCG (SEQ ID NO: 1184)eGRC_nm380.920.920.930.930.930.930.940.95GTAGACCTTGCTAATAACTTGCCTATAAGTTCCACAATACTCCCACTACG (SEQ ID NO: 1185)eGRC_nm390.900.910.890.910.900.910.910.89CGCAGAGTCTTGACCACAAGGAAAATCTTGTTTTTGAGCAATAACCCTTC (SEQ ID NO: 1186)eGRC_nm400.830.900.840.890.840.860.850.80CGTCAAGCTTTGTTGAGTCAGACAGTGTCTGTCCAAACTACTCAAGTCAG (SEQ ID NO: 1187)eGRC_nm410.980.980.980.980.980.980.980.98GGGCGAAGTCGCTGGTGCCAGAGTCAATGACACGGAGAGGAAACGCTTCG (SEQ ID NO:1188)eGRC_nm420.900.900.870.880.900.890.900.89TTTACTGATTTAG GATGTCGACCATCTAGTCTGCCAGAGCTGCAATAACG (SEQ ID NO: 1189)eGRC_nm430.880.910.910.890.900.910.890.91CGGCAAGTCCTATTGAGATTATAACAATGACACTGATAAAAAAGAAGATG (SEQ ID NO:1190)eGRC_nm440.920.910.910.920.920.890.920.93AGCACGTTCATGACCCTTGAAAGTCTTCGAAAACAGATTACTGGGCTTCG (SEQ ID NO: 1191)eGRC_nm450.930.920.890.870.920.900.890.87CGTGCACTCTGAACAAGCATTCATTTGGCTGCACAGGGCCAGATCAAGGT (SEQ ID NO: 1192)eGRC_nm460.920.930.900.920.920.910.910.88ACTAGCTTTGCGAAAGCCACAGGGAAGTGATCTTGGTTGTGCAGGTGTCG (SEQ ID NO: 1193)eGRC_nm470.930.910.930.910.930.940.930.94AAATGAATGTAGATACCATCTTAGCCAGGTGATGAAACAAACTGGTATCG (SEQ ID NO:1194)eGRC_nm480.900.900.890.900.890.900.900.88CGGAAATCAGAGGGAGAAGACGCATATCTTGTTTCAGTGAGGGTGATCCC (SEQ ID NO: 1195)eGRC_nm490.880.910.910.900.910.920.910.91CGGTCAGAGGGGACCATCTGTTTATCTTACAGGCTTAATATGATCACAGG (SEQ ID NO: 1196)eGRC_nm500.910.920.900.900.910.910.880.88TACCAGCCCTTCATTTCTTTGCTTTGACTCTTTAATTTCCAAGATAATCG (SEQ ID NO: 1197)eGRC_nm510.910.920.910.930.920.920.930.92CGGAAGGCTGGGGAAACAGGCTCTGCCCTATATCTGAGGGAAGTGTGCAT (SEQ ID NO:1198)nGRC_nm10.970.960.980.980.970.970.970.96CGCCAGGTTTCGAGATGAAATCTCCGCCCTGTAGCTCCGGACGTCCTCCA (SEQ ID NO: 1199)nGRC_nm30.970.950.970.960.960.950.970.97CGGCTAAGTCCCCACGTACGCCATTAAACAACGGTCAAATGGTAACATGT (SEQ ID NO: 1200)nGRC_nm40.940.960.920.960.960.920.960.95CTGCCCTTGGTCAGCACCGTGTAGGGCATGTGCTCACCCGCTG GAGATCG (SEQ ID NO: 1201)GRC_18nm0.920.910.910.930.940.920.930.94CGAAACAGATTGCATTTCCTAGAAGGCCCCCAGCGATGTGGATTGAAGCG (SEQ ID NO: 1202)nGRC_nm70.950.940.930.930.960.940.940.93CGGCTTGAGCGCCAGCAGCCTGCACAGGTTCCATGAGCTGGAGAGCTGCG (SEQ ID NO:1203)nGRC_nm80.890.910.890.900.900.890.920.91CGGACTACGAGTACCAGCACTCCAATTTGTATGCCATATCAGGTATGTGG (SEQ ID NO: 1204)nGRC_nm90.950.950.930.940.950.930.950.88AATACCTGGCACGCCAGGGTGATGCAACTGGGAGCTTCTGCACGTTCGCG (SEQ ID NO:1205)nGRC_nm100.970.960.980.970.970.970.980.98CAGCGCCCGTGTGATGATGATGCTCACGCTCCGGTGTGACACAGACGGCG (SEQ ID NO: 1206)nGRC_nm110.890.890.630.830.730.700.750.48CGGGAGGAGCTGGGTGGATACCTTTCTAACTTCCGAGGCTGGCTACTCCT (SEQ ID NO: 1207)nGRC_nm120.910.930.950.930.910.890.930.94CCCTCTGCCCAGCGCGTCTGGGACGTGTGCCCAAGAGCTTATTGAGAACG (SEQ ID NO: 1208)nGRC_nm130.960.960.970.970.970.970.960.95TCAGGAAATTGCGAAGAAATTCTGCGGCGGGTGCAGGATGCCCACCCTCG (SEQ ID NO:1209)nGRC_nm150.830.890.850.860.850.860.920.86CGTGGAGATGAACTAGAACAGGTATGAGGTTCTAGCAGAAGAAACATTTG (SEQ ID NO:1210)nGRC_nm160.960.970.970.970.970.970.970.97CGATATTAGAAAGGAGCTCAAGGTAGTACACTTCACGTGCCCCGGTAACG (SEQ ID NO:1211)nGRC_nm170.970.960.950.960.960.950.880.92CGGCACTTTCAACCAAACAGAGACACTCCGGCTCGTACACAACCAGCCGT (SEQ ID NO: 1212)nGRC_nm200.920.880.750.790.840.870.910.90CGCAATCCAGTCACACTTGTGAAAATGCTGAAGACGGTGGTTACGGAAGC (SEQ ID NO: 1213)nGRC_nm220.880.900.850.880.890.840.890.88CGCTGAGCCAGAACAATAGGACTTCTTCTGTAGTTGTGAAACTTGTCAGT (SEQ ID NO: 1214)nGRC_nm240.870.850.830.820.850.870.860.83GTACCAACTGAATTCAATTTAAAAACAAAGATGTCAGACATGCATCTTCG (SEQ ID NO: 1215)nGRC_nm250.860.870.890.890.880.920.900.89GTGTATGGATTCGGCATGGAGCCCTCAGCTGGCGGCTCTGGGTGCTGACG (SEQ ID NO: 1216)nGRC_nm260.920.920.910.900.900.910.920.86CGCACTTCTGTGCGCTCACTATGAGAAGCTGTGTTTACTCGCTCCGTGCT (SEQ ID NO: 1217)nGRC_nm280.960.930.960.950.960.950.960.94TCCCAGTCATTCTCGGGGTAAGTTCCGAAGTTGGAGGTGTCGCCTTCGCG (SEQ ID NO: 1218)nGRC_nm290.940.910.910.910.890.920.950.91CGTCCTCCGTCTGCCGCCCACTAATCGTTCCCCATACAGACTTCCTGGCG (SEQ ID NO: 1219)nGRC_nm300.920.920.810.830.860.860.900.77AGGTCACAGATGCAGACGTTTGCTCGAAGTGGCTGCCGAGCTCAGACCCG (SEQ ID NO:1220)nGRC_nm310.920.920.910.910.920.910.900.92GTGGAGGATCCAATTCTAAGACAGCTCATTCATTCACATGGCTGTTAGCG (SEQ ID NO: 1221)nGRC_nm320.920.920.920.900.920.930.920.91TTCTCAACACCAGTTTTCTGAGCAGGGTGAATAACTCTGCTCATACCTCG (SEQ ID NO: 1222)nGRC_nm330.870.910.830.880.860.870.870.78TCCTATTACTCCAGACGAATCTGTTTCATGTGCTGAAGCTCTCCCCTTCG (SEQ ID NO: 1223)nGRC_nm340.850.860.840.850.860.840.840.84AAAACCAAGTCTAGGATTTTTCCATGGATGGTTTCTCAGCCGCTCTCACG (SEQ ID NO: 1224)nGRC_nm350.900.890.890.900.910.920.920.90GGCTGTGGTTCTCTGCTTGTGCCCACTTTGTGTTTGTAAATAGCGAGTCG (SEQ ID NO: 1225)nGRC_nm360.840.900.910.910.920.910.910.91CGGGGGCTAGAGTTCATAATTTCTGGTAATCGCTCAACCCTGTGATTACG (SEQ ID NO: 1226)nGRC_nm370.870.900.910.910.910.920.920.91CGCTTTGCTTAGAGATCAACAGAGTGACATCCTAGGGTCTGAGCCTCAAC (SEQ ID NO: 1227)nGRC_nm380.880.890.830.810.860.840.830.83CAAAAGCCTGTGAGGAGCTCCTGGAAGACATTAAGTTCTCTACAGCAACG (SEQ ID NO:1228)nGRC_nm390.870.880.870.870.880.870.870.78CGCAGGAGTAAAATTGGGTAAAACAAGCACATGGGAACTGAGGCAATCTC (SEQ ID NO:1229)nGRC_nm400.890.900.880.890.890.880.870.83CGGGTGCAACTGGCACCAAGAACAACACCCATGCCCAGGTGACAACTGCG (SEQ ID NO:1230)nGRC_nm410.870.850.800.820.840.830.820.69CGTGTTCATAAATGAGTGCAGTGATATCAATTTAAGAACATCCATCATGT (SEQ ID NO: 1231)nGRC_nm420.890.900.900.890.900.880.880.88ATGTTTGTACACAGCTGCCTCCTTGACTGTAGTTGATTGGCCTCTGTGCG (SEQ ID NO: 1232)nGRC_nm430.940.690.920.920.870.910.880.95GAGACGAGCGTCTCAGACTTGAGGAAATACACGCGTGGAAGACGTGCGCG (SEQ ID NO:1233)nGRC_nm440.940.950.900.920.920.940.940.92GTTCTTCTCCGTGACAGGATGTTCTTTTCCGTGACAGGAAGTTCCGTCCG (SEQ ID NO: 1234)nGRC_nm450.950.940.930.920.940.930.940.91AAGTGGGATCCGCAAGATGATGGATGAGTTTGAGGTAGACCCCTTTCCCG (SEQ ID NO: 1235)nGRC_nm460.900.900.880.880.880.870.910.84TGACGCTGTATTTCCTGAAACTGCTCAGCAAGATTTCCAGCTATCCAGCG (SEQ ID NO: 1236)nGRC_nm470.850.900.900.890.870.890.870.90CGGTCAGTTCCTGTGAGGAGGAAACAATGATACTGCATTATAGACATCGT (SEQ ID NO: 1237)nGRC_nm480.880.880.870.890.870.880.860.86CGGGGAGGGACTAGATCAGAAGAGATCAAGGGCTCTATTCAGGAACGTTG (SEQ ID NO:1238)nGRC_nm490.980.980.970.970.980.970.980.97CGTGGGCATCACGTAAGCAGCACACTAGGAGGCCCAGGCGCAGGCAAAGA (SEQ ID NO:1239)nGRC_nm500.840.890.900.920.900.890.890.90CAAATCACTGTAGTTCAGACAAAACCTTCATACCATTTTATTATTTAACG (SEQ ID NO: 1240)
TABLE 4HT-Cell MarkerBaso-Eosino-Neutro-Clas-philphilphilsicalNon-NKMarker-TargetGranulo-Granulo-Granulo-Mono-clas-clas-IDIDSYMBOLAccessioncytescytescytescytessicalsicalOTL_nm18cg03388043CCDC57NM_1980820.950.960.970.960.960.84 OTL_nm19cg19163395HDAC5NM_0010150530.970.950.970.920.910.94 OTL_nm5cg24612198CD3ENM_0007330.920.950.930.940.930.89 OTL_nm4cg07545925CD3GNM_0000730.900.890.900.920.890.87 OTL_nm22cg24441810TMEM177NM_0011051980.860.890.920.910.920.90 OTL_nm23cg17311865——0.930.930.910.910.890.89 OTL_nm24cg17615629HLA-ENM_055160.900.880.930.940.920.74 OTL_nm25cg08659421IL32NM_0010126320.890.900.910.900.900.80 OTL_nm26cg07930673——0.890.880.880.890.900.79 OTL_nm27cg10111816CDR2NM_0018020.820.750.840.850.860.84 OTL_nm28cg25643644CD3DNM_0007320.880.890.890.910.880.57 OTL_nm29cg07630255MPINM_0024350.870.890.890.890.870.77 OTL_nm30cg18222759——0.920.900.920.900.940.90 OTL_nm31cg02772121TRIMI5NM_0332290.890.850.740.870.850.74 OTL_nm32cg03274669——0.870.870.860.850.890.61 OTL_nm33cg25276892TNRC6BNM_0010248430.760.580.870.890.910.85 OTL_nm34cg09232358——0.880.890.890.850.860.85 OTL_nm35cg24215459TNIP3NM_0011288430.820.840.870.880.860.55 OTL_nm36cg26137915——0.880.890.890.880.870.57 OTL_nm37cg04403423ATPIAINM_0011602330.860.890.890.900.890.81 OTL_nm38cg20567280——0.810.840.850.830.810.76 OTL_nm39cg27111890UBASH3ANM_0010018950.650.860.890.890.880.84 OTL_nm40cg10505658CCDC57NM_1980820.820.730.810.860.820.58 OTL_nm41cg24961795PLCGINM_0026600.860.860.850.840.820.83 OTL_nm42cg00027570CD2NM_0017670.790.840.860.880.840.81 OTL_nm43cg23318020——0.810.850.850.860.850.51 OTL_nm44cg14841483ACLS6NM_0010091850.800.790.770.820.840.78 OTL_nm45cg03002526HACE1NM_0207710.850.860.890.850.850.78 OTL_nm46cg17922695SEPT9NM_0011134920.840.710.730.870.680.68 OTL_nm47cg03040292——0.630.840.900.890.870.59 OTL_nm48cg11753157BCL11BNM_0228980.710.760.800.790.750.87 OTL_nm49cg07203767——0.810.840.850.860.830.66 OTL_nm50cg15227911CHD3NM_0010052710.700.720.820.770.720.78 OTL_nm51cg01830053——0.770.610.710.780.790.73 OTL_nm52cg26271776——0.790.830.810.810.770.79 OTL_nm53cg16239536HMHAINM_0122920.840.820.830.820.810.58 OTL_nm54cg08445740FAM71BNM_1308990.790.840.850.840.810.56 OTL_nm55cg27666046SECTM1NM_0030040.700.730.730.760.720.57 OTL_nm56cg26053876——0.810.830.790.770.720.68 OTL_nm57cg06110802RPS3ANM_0010060.790.770.850.820.830.83 OTL_nm58cg07555731OR5AU1NM_0010047310.720.690.720.690.690.61 OTL_nm59cg13827677SETNM_0030110.620.560.720.800.740.61 OTL_nm60cg24033471CACNA1CNM_0011298440.660.680.710.710.660.52CD4+ CD4+CD8+CD4+Th Cen-ThCyto-Marker-TargetB-ThCD4+CD4+tralEffect.toxicNK T-DiscoveryIDIDCellsnaiveTh1Th2Mem.Mem.T-CellsCellsFragmentOTL_nm18cg0338-0.970.070.020.020.030.030.030.07GGCTTGCGTAGT8043CAAGGCTGCCCGCGTGCCACGTGTGGTGGACAGCATCG (SEQ IDNO: 1241) OTL_nm19cg1916-0.860.180.020.020.030.020.180.05CGCGCCTAGCTG3395GCACTCCATTCATTGCGGACACAGCCGAGCCCTCCGGG (SEQ IDNO: 1242) OTL_nm5cg2461-0.940.140.040.040.050.070.090.08AGTCATCTGTTT2198TGCTTTTTTTCCAGAAGTAGTAAGTCTGCTGGCCTCCG (SEQ IDNO: 1243) OTL_nm4cg075-0.880.080.040.040.040.050.040.06CGGAAAAACAA45925AAGGCATCTGCACCTGCAGCCCTGCTGAGGCCCCTGCTG (SEQ ID NO:1244) OTL_nm22cg244-0.820.070.050.050.040.040.050.10GCATGGGTTCTG41810ATGGGGGCCCTGCCATAGGCCGCCTGGTGACCCACGCG (SEQ ID NO:1245) OTL_nm23cg1731-0.820.180.000.030.050.020.120.25CGCACATCTCAT1865CTAATGCCATGGTATTCCTTATTTCGTGTCAGCCCTTCC (SEQ ID NO:1246) OTL_nm24cg1761-0.770.080.040.050.020.040.030.08CGCACCCAGCCG5629CACCTACTCTTTTGTAAAGCACCTGTGACAATGAAGGA (SEQ IDNO: 1247) OTL_nm25cg086-0.830.160.060.050.040.060.060.07CAAGCCCCAGG59421GCTCCTTGAGGAAACAACAGGGGTGCCAGACGTGGCCCG (SEQ IDNO: 1248) OTL_nm26cg0793-0.890.090.090.090.080.100.090.16CGGGGGAGGCT0673GCTGAGTGGTTTTGAAATTATACAGAGCTGGATTTGAC (SEQ ID NO:1249) OTL_nm27cg101-0.830.080.040.050.040.070.050.06CTTCTGTCGTTT11816CAATTGGCATCTGGTGAACTATGCCTAACAGCTTAACG (SEQ ID NO:1250) OTL_nm28cg2564-0.900.100.060.070.080.090.060.08GGAGTTCATTGC3644TGGGTGTGACTGGAGAGGTCAGGCAGGAGCTCTCATCG (SEQ ID NO:1251) OTL_nm29cg0763-0.820.080.070.070.060.090.120.16AGATTTTCCCTA0255GCCCTGCAGCTGCCCTCCATGGATGGACTTGTATCTCG (SEQ ID NO:1252)OTL_nm30cg1822-0.810.190.110.100.110.100.160.17CTGCTGTTCAGG2759GAAATGGCTTCCTTTCAGATGTGTTTCTCATAGTCTCG (SEQ ID NO:1253) OTL_nm31cg027-0.830.100.050.060.090.060.100.10GGCGGGACGCT72121GTTTCGACACTGCAGGTAGGGTGTAAGGATTGCTCATCG (SEQ ID NO:1254) OTL_nm32cg032-0.910.090.050.040.050.050.120.23TGCCTGAAATGA74669TACAGTAGIGTATAAACCAAGTATCTCTGCTTGCATCG (SEQ ID NO:1255) OTL_nm33cg2527-0.730.030.030.030.040.040.100.10CGGTTTGCATCT6892CCAGCCCCCGCGGCTCACAGGCCGTGTAACTTCACTGC (SEQ ID NO:1256) OTL_nm34cg0923-0.890.220.100.120.130.130.110.10CGGCCATATTCT2358GGCAGGGTCAGTGGCTCCAACTAACATTTGTTTGGTAC (SEQ ID NO:1257) OTL_nm35cg2421-0.630.090.040.050.050.060.040.05CGAAGAATTGTA5459TTTGCATGTCTGAAATGAAAGCCCAGAGAATAGGGTGG (SEQ IDNO: 1258) OTL_nm36cg2613-0.860.120.110.100.100.130.100.17TGGAAACCCCTT7915CAGCAGCGTATGGTGCTGGGGACCTTCTGGGGAGATCG (SEQ ID NO:1259) OTL_nm37cg044-0.640.080.130.090.080.150.110.22AAAGCATGCAG03423CGTGGAGGGCTGGTCCAGGTCAGGTGGCATCAAAGAGCG (SEQ IDNO: 1260) OTL_nm38cg2056-0.790.110.060.080.070.080.080.20CGGTACCCCAAA7280ATTTGGTGCTTTGACATGCTGAACTAGAGAAGCAGCCG (SEQ ID NO:1261) OTL_nm39cg2711-0.920.140.130.130.120.140.120.16CGCATTCTTGCT1890CCCGAATACTAGCCAAGTCCCTACAGAGGCTGATCCCG (SEQ ID NO:1262) OTL_nm40cg1050-0.830.110.050.050.040.060.080.11GCAGCCTCTGGG5658TGGGTGGCGGAGGCTGAGGCGATGCTGTCCACCACACG (SEQ IDNO: 1263) OTL_nm41cg249-0.770.160.090.080.100.110.110.15CGAGTCTGAACC61795TCTCAACTCAGAAAACACCAGAGAAAAAGTGTGGAG (SEQ IDNO: 1264) OTL_nm42cg0002-0.820.170.100.110.100.140.140.15CGGTGTTTCTGC7570ACTGTTGATCCTGCTCTCGTCTCTGGCTACCCCCACTG (SEQ ID NO:1265)OTL_nm43cg2331-0.830.110.080.040.070.090.090.17CGCTGAAACTTA8020GCAGGCACTCAGTAAATATTTTGCTAAGCAGTTAAAAC (SEQ ID NO:1266) OTL_nm44cg148-0.840.110.090.080.070.110.130.20CGCCTGCAGAA41483AGTGATCTTTCCGAGACAGGACGATGTGCTCATCTCCTT (SEQ IDNO: 1267) OTL_nm45cg0300-0.810.180.160.120.130.100.160.19AGTCAAAGTCA2526AATCATGGGTAGTTCCGTCACTACAAAGTGAGCCACG (SEQ IDNO: 1268) OTL_nm46cg1792-0.680.080.030.040.030.060.040.13CGTCCTGAGTTC2695CCAGACGTCATAGGTGCTTGCTCAACGAGTGTTTGAAT (SEQ ID NO:1269) OTL_nm47cg0304-0.630.090.070.050.050.060.120.20CTACCAAAGCAC0292TGGAGCTCATAACAAGCTGCCTGTCCTTGGCCACCTCG (SEQ ID NO:1270) OTL_nm48cg1175-0.700.080.080.050.050.070.090.23CCACTGGAGATA3157TACTCTACCCTGGGGAGTTAAGATAATTGTGAGCACCG (SEQ ID NO:1271) OTL_nm49cg0720-0.840.150.120.130.120.150.130.14CGGGCTGGGGA3767GGTGTAAAGACAAATCCCGGTGACCCTGGCCCTAAAAAG (SEQ IDNO: 1272) OTL_nm50cg152-0.820.060.050.050.050.060.120.21CGCGCGTGCTTT27911TGAGAAGGCATATGCTGGGTGTGTCTGTCTGTGCCTAT (SEQ ID NO:1273) OTL_nm51cg0183-0.720.040.020.020.030.040.100.24ACGCTAGTGCAG0053CACTTTTGAAAGTAAAAAGCACTTTGCAATAATTAACG (SEQ ID NO:1274) OTL_nm52cg2627-0.710.220.110.110.110.110.190.14CGTCGTCCTGGC1776TAGGATCTAGCATCTCAGTGCAAATGGGCTATGTAAG (SEQ ID NO:1275) OTL_nm53cg1623-0.740.140.090.110.120.150.150.23AGCCCGGGGTG9536CAGGACTCAGACAGAAACCTCAGGGAGGCGGGGCTGACG (SEQ IDNO: 1276) OTL_nm54cg0844-0.640.110.120.130.140.160.150.15CGGTGATTCAAG5740ACCTCCAAGAATTCCTGTGGTTCCCAGTAAATCCCCAC (SEQ ID NO:1277) OTL_nm55cg2766-0.600.140.030.030.030.040.070.11CGAGGACGCCTT?6046AGGGACGTTTTGGGGCTTAAAGCCACTAAAGACGTTTC (SEQ ID NO:1278) OTL_nm56cg2605-0.750.190.080.170.110.140.140.13CGCCCACACAGT3876TTGGAGTTAAACAGATCTCAACAAATGAACACAGTTAT (SEQ ID NO:1279) OTL_nm57cg0611-0.660.180.210.200.220.210.150.23CTGGTTCATCTC0802AGGTGTTGTTGCTTTGTGAACATTCACTAAGCTCTACG (SEQ ID NO:1280) OTL_nm58cg0755-0.550.160.090.080.120.120.150.12TCTTCTTAGTGA5731GCATGCTCATAGCTAACCTTCTTTGAACTTCCTCAACG (SEQ ID NO:1281) OTL_nm59cg1380.720.120.160.150.130.180.130.21CTATCGCTTGGG27677GCTGTTGTGAGGCCTCGGTGAGATAACCGTGCCATGCG (SEQ ID NO:1282) OTL_nm60cg240-0.560.150.100.130.130.170.120.13TCTCTCCTTTGC33471TATGGGAGGGCTTGAATCTGTGGCAGCCTTCAAAACCG (SEQ ID NO:1283)
TABLE 4IMDSC (myeloid-derived suppressor cells) MarkerNon-Baso-Eosino-Neutro-Clas-clas-philphilphilsicalsicalMarkerTargetAcces-Granulo-Granulo-Granulo-Mono-Mono-IDIDSYMBOLsioncytescytescytescytescytesMDSC_nm1cg1031-UPP1NM_00-0.970.950.950.950.9377171287426 MDSC_nm2cg0936-DAXNM_0011-0.960.960.920.880.90500241969 MDSC_nm3cg2249-M4SF19NM_001-0.940.950.950.920.806559204897 MDSC_nm4cg2495-SRCNM_00-0.790.820.870.770.5463915417 MDSC_nm5cg2278-TYH3NM_02-0.910.840.890.830.8489535250 MDSC_nm6cg0648-CLCN7NM_00-0.910.880.870.850.7796151114331 MDSC_nm7cg189-——0.930.900.920.650.6395788 MDSC_nm8cg1315-SMURF1NM_00-0.910.910.910.810.8125011199847 MDSC_nm9cg1812-——0.880.890.900.900.909996 MDSC_nm10cg2070-——0.970.810.020.510.590740 MDSC_nm11cg023-ZC3H8NM_03-0.900.910.920.870.88411392494 MDSC_nm12cg1998-SYNPONM_0011-0.840.900.820.720.76491109974 MDSC_nm13cg221-ATP6V1E2NM_08-0.900.870.900.870.84374710653 MDSC_nm14cg0882-SNX29NM_03-0.840.770.510.720.7628912167 MDSC_nm15cg0047-ATN1NM_0010-0.890.850.380.550.56660807026 MDSC_nm16cg2027-CTSZNM_00-0.890.890.900.720.5687901336 MDSC_nm17cg0869-——0.910.910.920.790.627732 MDSC_nm18cg008-CMIPNM_03-0.870.820.820.870.87642930629 MDSC_nm19cg1444-GPNMBNM_0010-0.870.900.910.730.59437605340 MDSC_nm20cg0094-——0.880.880.880.880.875409 MDSC_nm21cg0336-PDXKNM_00-0.860.810.650.760.7569923681 MDSC_nm22cg0417-DOT1LNM_03-0.720.080.210.730.3835862482 MDSC_nm23cg0042-——0.850.890.870.870.826089 MDSC_nm24cg1086-CGF3NM_00-0.340.470.600.580.6542006315 MDSC_nm25cg0425-——0.850.830.820.630.402044 MDSC_nm26cg0190-——0.840.850.850.830.825967 MDSC_nm27cg035-——0.900.890.860.660.7100164 MDSC_nm28cg0173-NANOGNM_02-0.900.900.880.570.5842404865 MDSC_nm29cg0912-TRIMNM_17-0.770.760.700.810.7975921982 MDSC_nm30CG090-CCR1NM_00-0.820.870.890.870.83886251295 MDSC_nm31cg1769-APBB2NM_0011-0.880.890.860.820.76921466050 MDSC_nm32cg0793-MFSD12NM_0010-0.710.510.900.900.85780342680 MDSC_nm33cg2728-HS1BP3NM_02-0.810.850.850.680.4623972460 MDSC_nm34cg0135-RXRBNM_0012-0.840.870.860.880.87967670401 MDSC_nm35cg054-PHF15NM_01-0.750.780.760.660.63761825288 MDSC_nm36cg1481-SORCS2NM_02-0.800.830.850.820.7424740777 MDSC_nm37cg0821-——0.890.890.910.660.450681 MDSC_nm38cg1707-ITGAENM_00-0.960.670.030.420.4940142208 MDSC_nm39cg1532-MRASNM_0010-0.840.850.810.560.48000185049 MDSC_nm40cg1939-——0.850.860.860.830.869285 MDSC_nm41cg2116-——0.810.850.850.770.784050 MDSC_nm42cg2120-RGIC1NM_00-0.790.840.820.860.8845301031711 MDSC_nm43cg072-CSF1RNM_00-0.800.870.860.830.62600171288705 MDSC_nm44cg0619-AC-—0.870.820.810.870.863597104809.3 MDSC_nm45cg2617-——0.730.670.790.720.514398 MDSC_nm46cg2458-SH3RF3NM_001-0.830.840.850.810.727185099289 MDSC_nm47cg0582-MFSD7NM_03-0.890.790.630.600.3971902219 MDSC_nm48cg0317-——0.800.790.730.580.426993 MDSC_nm49cg0337-MBN1.2NM_14-0.720.680.690.700.6923344778 MDSC_nm50cg2187-SPARCNM_00-0.800.730.320.480.4474643118 MDSC_nm51cg0985-FKBP2NM_0011-0.900.720.820.710.36472635208 MDSC_nm52cg1649-BCAT1NM_00117-0.860.800.730.610.5102098091 MDSC_nm53cg181-——0.800.750.640.520.4414313 MDSC_nm54cg223-——0.640.430.500.490.4107974 MDSC_nm55cg191-AMPD3NM_00-0.630.060.070.440.37324620480 MDSC_nm56cg1222-MYO9BNM_00-0.680.390.760.630.5399791130065 MDSC_nm57cg0609-——0.820.530.470.480.333152CD4+ThNKNKCD4+Cen-MarkerTargetclas-brightNKB-ThCD4+CD4+CD4+tralIDIDsicalNKB_1NKB_2brightCellsMDSCnaiveact.Th1Th2Mem.MDSC_nm1cg1031-0.950.960.930.940.970.150.950.920.930.950.967717 MDSC_nm2cg0936-0.960.960.950.950.960.210.960.950.960.970.975002 MDSC_nm3cg2249-0.760.910.860.880.820.280.930.910.930.940.936559 MDSC_nm4cg2495-0.930.910.780.850.560.100.940.750.820.820.856391 MDSC_nm5cg2278-0.950.890.880.890.940.290.940.900.920.920.948953 MDSC_nm6cg0648-0.920.910.930.920.930.350.930.920.920.920.929615 MDSC_nm7cg189-0.950.950.970.960.980.210.980.870.900.920.9595788 MDSC_nm8cg1315-0.910.920.890.910.920.360.910.900.910.900.912501 MDSC_nm9cg1812-0.890.890.890.890.910.370.920.900.890.890.919996 MDSC_nm10cg2070-0.980.980.950.960.980.170.840.970.980.980.970740 MDSC_nm11cg023-0.900.900.840.870.900.280.920.880.860.880.9041139 MDSC_nm12cg1998-0.890.920.890.900.910.290.920.890.900.890.914911 MDSC_nm13cg221-0.870.890.890.890.870.190.880.890.880.880.8837471 MDSC_nm14cg0882-0.900.890.900.900.910.270.910.900.860.890.872891 MDSC_nm15cg0047-0.920.900.920.910.880.250.910.860.890.890.906608 MDSC_nm16cg2027-0.890.860.830.840.470.330.900.860.870.890.898790 MDSC_nm17cg0869-0.880.890.880.890.830.230.910.820.850.870.857732 MDSC_nm18cg008-0.890.900.880.890.910.280.920.730.730.770.7864293 MDSC_nm19cg1444-0.870.830.810.820.840.220.930.810.870.880.884376 MDSC_nm20cg0094-0.870.890.810.850.860.180.880.800.810.840.845409 MDSC_nm21cg0336-0.860.830.870.850.890.250.880.810.840.830.836992 MDSC_nm22cg0417-0.900.960.950.950.780.210.980.920.960.960.963586 MDSC_nm23cg0042-0.850.790.750.770.620.330.890.810.840.850.866089 MDSC_nm24cg1086-0.880.880.860.870.870.330.920.890.930.930.934200 MDSC_nm25cg0425-0.870.900.890.900.880.170.890.800.850.870.852044 MDSC_nm26cg0190-0.870.880.870.870.850.330.910.860.870.890.845967 MDSC_nm27cg035-0.840.740.800.770.870.230.910.750.860.890.9100164 MDSC_nm28cg0173-0.870.810.740.780.870.260.900.790.830.840.844240 MDSC_nm29cg0912-0.830.860.790.820.920.280.910.820.880.880.887592 MDSC_nm30CG090-0.810.640.740.690.850.280.880.830.860.850.8688625 MDSC_nm31cg1769-0.890.880.870.880.900.160.910.700.760.770.749214 MDSC_nm32cg0793-0.900.880.890.880.840.210.910.760.760.790.837803 MDSC_nm33cg2728-0.840.810.880.840.810.250.850.810.820.830.822397 MDSC_nm34cg0135-0.850.830.840.830.820.250.860.700.750.740.759676 MDSC_nm35cg054-0.840.850.820.840.850.260.880.800.810.820.8176182 MDSC_nm36cg1481-0.830.750.710.730.830.240.870.750.790.790.782474 MDSC_nm37cg0821-0.850.820.820.820.830.130.880.730.820.830.850681 MDSC_nm38cg1707-0.840.890.890.890.980.190.930.680.930.920.924014 MDSC_nm39cg1532-0.810.810.810.810.810.280.870.840.800.820.830001 MDSC_nm40cg1939-0.860.880.850.860.830.280.880.660.760.690.779285 MDSC_nm41cg2116-0.830.840.850.850.820.250.910.730.690.800.824050 MDSC_nm42cg2120-0.780.850.850.850.850.210.850.670.630.680.714530 MDSC_nm43cg072-0.770.830.840.830.820.220.880.630.670.660.6760017 MDSC_nm44cg0619-0.840.900.920.910.550.160.780.420.620.650.453597 MDSC_nm45cg2617-0.790.830.840.840.700.140.840.610.650.570.644398 MDSC_nm46cg2458-0.700.750.730.740.830.190.840.570.540.640.667185 MDSC_nm47cg0582-0.880.910.870.890.830.250.900.710.770.770.797190 MDSC_nm48cg0317-0.830.840.790.810.810.180.880.780.750.820.816993 MDSC_nm49cg0337-0.830.790.800.790.760.190.700.880.800.800.742334 MDSC_nm50cg2187-0.830.840.830.830.840.200.860.740.750.780.797464 MDSC_nm51cg0985-0.880.880.820.850.550.190.910.680.710.750.784726 MDSC_nm52cg1649-0.770.860.800.830.870.210.870.740.610.800.770209 MDSC_nm53cg181-0.830.830.840.840.350.210.880.700.640.770.7214313 MDSC_nm54cg223-0.740.690.690.690.690.170.810.710.760.810.7707974 MDSC_nm55cg191-0.840.870.810.840.510.150.730.820.760.810.7732462 MDSC_nm56cg1222-0.630.760.660.710.710.150.880.740.770.730.729979 MDSC_nm57cg0609-0.780.850.830.840.750.140.900.590.590.690.683152CD4+CD8+CD8+CD8+ThCD4+Cyto-CD8+ThThMarkerTargetEffect.NKTCD4+toxicnaiveCD8+CentralEffectIDIDMem.cellsTFHT-CellsT8n_1act.Mem.Mem.TEMRAMDSC_nm1cg1031-0.950.830.900.960.940.950.940.950.947717 MDSC_nm2cg0936-0.960.920.940.970.960.950.960.960.965002 MDSC_nm3cg2249-0.940.790.910.870.930.920.820.880.606559 MDSC_nm4cg2495-0.840.800.620.930.910.830.880.870.916391 MDSC_nm5cg2278-0.950.880.900.950.940.910.880.930.958953 MDSC_nm6cg0648-0.920.910.910.930.900.920.900.910.909615 MDSC_nm7cg189-0.950.880.910.950.960.830.920.880.8795788 MDSC_nm8cg1315-0.910.900.880.920.910.900.910.910.902501 MDSC_nm9cg1812-0.900.900.900.910.880.900.870.880.879996 MDSC_nm10cg2070-0.980.940.970.960.930.970.980.970.980740 MDSC_nm11cg023-0.880.840.890.910.890.880.890.830.8341139 MDSC_nm12cg1998-0.900.890.910.920.900.890.890.850.894911 MDSC_nm13cg221-0.880.890.890.890.880.890.860.860.8637471 MDSC_nm14cg0882-0.880.780.880.910.910.910.900.880.872891 MDSC_nm15cg0047-0.900.880.890.900.900.880.890.890.906608 MDSC_nm16cg2027-0.890.840.870.890.900.850.870.840.868790 MDSC_nm17cg0869-0.870.870.860.860.910.800.820.800.787732 MDSC_nm18cg008-0.770.760.680.870.910.800.890.860.8764293 MDSC_nm19cg1444-0.860.780.840.890.860.810.780.810.834376 MDSC_nm20cg0094-0.850.780.830.860.860.790.800.780.645409 MDSC_nm21cg0336-0.840.840.800.870.870.840.860.790.846992 MDSC_nm22cg0417-0.960.920.930.970.950.920.880.940.973586 MDSC_nm23cg0042-0.870.760.810.890.840.830.800.780.836089 MDSC_nm24cg1086-0.940.870.870.930.900.920.860.910.894200 MDSC_nm25cg0425-0.810.820.710.910.870.850.900.820.852044 MDSC_nm26cg0190-0.810.760.890.860.870.860.870.710.455967 MDSC_nm27cg035-0.910.750.790.900.800.780.760.780.7800164 MDSC_nm28cg0173-0.820.790.790.860.870.800.770.840.764240 MDSC_nm29cg0912-0.860.800.820.660.440.800.830.890.867592 MDSC_nm30CG090-0.860.770.830.850.860.840.810.490.8488625 MDSC_nm31cg1769-0.760.760.740.830.880.740.780.750.789214 MDSC_nm32cg0793-0.810.800.850.840.900.700.840.720.687803 MDSC_nm33cg2728-0.830.840.820.850.830.810.790.780.772397 MDSC_nm34cg0135-0.750.730.610.860.850.780.780.790.829676 MDSC_nm35cg054-0.810.760.770.870.870.850.790.790.8376182 MDSC_nm36cg1481-0.790.680.770.830.820.790.790.760.812474 MDSC_nm37cg0821-0.830.800.750.840.870.720.750.690.760681 MDSC_nm38cg1707-0.910.860.810.800.840.560.800.830.964014 MDSC_nm39cg1532-0.830.780.830.800.780.830.790.760.800001 MDSC_nm40cg1939-0.730.760.690.790.870.610.660.670.779285 MDSC_nm41cg2116-0.740.730.750.820.870.720.780.620.524050 MDSC_nm42cg2120-0.690.700.610.760.850.730.710.700.784530 MDSC_nm43cg072-0.680.610.680.790.860.620.690.670.6760017 MDSC_nm44cg0619-0.130.790.550.520.910.380.880.820.673597 MDSC_nm45cg2617-0.610.710.590.760.840.650.720.620.604398 MDSC_nm46cg2458-0.630.520.540.770.820.570.660.550.567185 MDSC_nm47cg0582-0.790.780.740.830.890.750.770.750.797190 MDSC_nm48cg0317-0.810.780.700.850.870.850.820.800.776993 MDSC_nm49cg0337-0.870.680.720.560.850.880.810.850.862334 MDSC_nm50cg2187-0.800.750.780.820.870.690.780.760.767464 MDSC_nm51cg0985-0.790.680.700.820.890.700.730.690.624726 MDSC_nm52cg1649-0.720.680.770.790.890.720.670.610.590209 MDSC_nm53cg181-0.700.710.730.800.870.700.790.690.6314313 MDSC_nm54cg223-0.810.650.730.810.770.730.700.730.7307974 MDSC_nm55cg191-0.760.680.820.860.870.840.850.780.7732462 MDSC_nm56cg1222-0.720.740.660.790.840.750.720.700.619979 MDSC_nm57cg0609-0.630.610.450.760.880.650.690.520.683152CD8+MarkerTargetNKTNKT-DiscoveryIDIDcellsCellsFragmentMDSC_nm1cg1031-0.880.89CGCCTGGAGC  7717CCGCCTCCAGCGCCTCCCACTGCAGACGTCTGTCGCTCTC (SEQID NO: 1284) MDSC_nm2cg0936-0.950.96CGCCGGGCCA   5002ACACAGGATCT  GATAGTGCAG   GGTCAACGCCT   ACGTGGGA(SEQ ID NO:  1285) MDSC_nm3cg2249-0.590.72CGCGCCCCCAC6559GCCCCTGCCCA  CAGGCCTGCAT   TGAAGGCGCTT  CCGCTC (SEQ ID NO: 1286) MDSC_nm4cg2495-0.810.87AAGGATGGCA6391TCCATCCGTAAAGGGCTTCCTCGGTCCAGCGCCAGGAACG(SEQID NO: 1287) MDSC_nm5cg2278-0.930.93CGCGGCCGAG8953CTGTCTGTCCAAGCCTGGGCCCCAGCACCCAGCGCAAGCT(SEQ ID NO:1288) MDSC_nm6cg0648-0.910.91GAGTGTTGGCT9615CACGTGTTCCTGAGCCTGTCTGTTTTTAGTTAGTGTCCG (SEQID NO: 1289) MDSC_nm7cg189-0.850.90CGGGCAGATA95788CGAGCAGATTGACTCGCCAGGACTGTCATTGGGCCACCGC(SEQ ID NO:1290) MDSC_nm8cg1315-0.910.91CTGACCTCATC2501CCGGAGGCCGCTTCAGTTCTCGAATGGATGTCTCTTCCG (SEQID NO: 1291) MDSC_nm9cg1812-0.890.90CGCCACAGGA9996ATGGCTCTTATGATCCTTTTGGTGGCTAGATTTCTGAAA (SEQID NO: 1292) MDSC_nm10cg2070-0.970.98CCTCCTGTGAG0740CAACCTTTCGGCGTCTGCAGAGCTCGTGGCGTAAGAGCG (SEQID NO: 1293) MDSC_nm11cg023-0.820.85CGACAGCAAT41139CCCGTGAGAAACTGTGGGACAGAACCACCCAGCTAAGCAG(SEQ ID NO:1294) MDSC_nm12cg1998-0.880.89CGGCAAAGGC4911AGCCAATTGCTTGGCTGACGAAGCCAGGAAAATCCCACAT(SEQ ID NO:1295) MDSC_nm13cg221-0.880.88AAAGAATGAG37471GTCACTGTCACCAATGAAGTCACCACTGCATGATTCATCG(SEQ ID NO:1296) MDSC_nm14cg0882-0.870.88TGTGGATTCCT2891CCAAACTGTGATTGCTACATCTTAATTTTCAGCAGGACG (SEQID NO: 1297) MDSC_nm15cg0047-0.900.90AGATACTGGG6608GGACGTGCTTCGGTTGTCCTGGTCGATATCCCTGGGTCG (SEQID NO: 1298) MDSC_nm16cg2027-0.860.88TGGCAAGTCGC8790TCATGGAAACCATTAGTGTCCATCAGTCATCAGAAGGCG (SEQID NO: 1299) MDSC_nm17cg0869-0.750.76CCATAGCACCC7732CCATAATAAAGCAGCCCGTGAGGGCAGCCTGGCTGTTCG(SEQ ID NO:1300) MDSC_nm18cg008-0.830.84CGGAGCAGGC64293CACAGTCAGGGTGGAAGAAAACGAGGGAAGACTGAGAAAC(SEQ ID NO:1301) MDSC_nm19cg1444-0.770.85CGGCACTGCCT4376GATCTGGTCTCTCAAGTTCAACCTCTTACAACTCATGTG (SEQID NO: 1302) MDSC_nm20cg0094-0.790.80GCCTTGTCCTG5409GGGCTGAGCAGTGGTGCAACCCAGCCCTGAGCAATTCCG(SEQ ID NO:1303) MDSC_nm21cg0336-0.850.85CCACCTGAGGT6992GAGCAATCAGAGGACACCCCTCGAGTCACTGGGAGTTCG (SEQID NO: 1304) MDSC_nm22cg0417-0.900.96CGGCACAGTCC3586CGCCCACCACTAGAAAGCCCGCTCCCGCCAGCTCTCGCC (SEQID NO: 1305) MDSC_nm23cg0042-0.740.85AGCTTTGTATA6089GATGCATGCACTTGGAAACCAGCAAAGCTAAAAATACCG(SEQ ID NO:1306) MDSC_nm24cg1086-0.930.93CGCAGGAGCG4200CACACACGTTCCCACACGCCACTCAATTCCAGAACAACGG (SEQID NO: 1307) MDSC_nm25cg0425-0.850.86GTATGTGTGAG2044TCAATCTAATGTGCCCTCCCTCAGCATAATCCTGTCACG (SEQID NO: 1308) MDSC_nm26cg0190-0.530.66TGGAAATCTCT5967TTCGTCAAGGCCTCTAGTGACCGCTGGGGATTCTTCTCG (SEQID NO: 1309) MDSC_nm27cg035-0.740.86TCATACATTTC00164AACTTGCTGCTGTTCTGAGTAGCGTGATGAAATCTTGCG (SEQID NO: 1310) MDSC_nm28cg0173-0.810.82CGGAGTAGTCT4240TGAAAGACATGACAAATCACCAGACCTGGGAAGAAGCTA(SEQ ID NO:1311) MDSC_nm29cg0912-0.850.90GGCGGCGGGG7592CACAGCGTGGGGGTGTGCAGTGACTGAGAGATGGTTCACG(SEQ ID NO:1312) MDSC_nm30CG090-0.680.64GAATGATCTCT88625GCACTGTAGGACATCCTTGGCCCTGCCTACCAAATGACG (SEQID NO: 1313) MDSC_nm31cg1769-0.800.78CGGCTGTTCCA9214GACCCTAATGAGTTCAGTTGTCCTACAAAGCAGGAAGAG (SEQID NO: 1314) MDSC_nm32cg0793-0.710.69CGGGGTGTCAC7803TCCTACAAGACAAGAAAAGCCCAGGATTGCTGGCCAATG (SEQID NO: 1315) MDSC_nm33cg2728-0.800.82TACACAGTTC2397CCTGCACACACTCGGCTAACTGTGACCAGGGTGAGAGCG (SEQID NO: 1316) MDSC_nm34cg0135-0.810.80ATGACCCTGTG9676ACTAACATCTGTCAGGCAGCTGACAAACAGCTATTCACG (SEQID NO: 1317) MDSC_nm35cg054-0.810.81CTGTTAGGCAG76182AGCAGCCTAATGGGAGCAGTGTGACTCATGGACCTCACG (SEQID NO: 1318) MDSC_nm36cg1481-0.770.76TCATCCAAGCT2474TGTGTGAGTCACAATGAGCAGAAAGCATTCTTCCACCCG (SEQID NO: 1319) MDSC_nm37cg0821-0.640.77CGGCCCCAGC0681ACTGCAAAGCTGTCATCGCTCCTCTCCAGGGAGCCATCCT (SEQID NO: 1320) MDSC_nm38cg1707-0.850.89CGGCCCATGTG4014TCGCACTCGCCTCGGCTCCCACACAGCCGCCTCTGCTCC (SEQID NO: 1321) MDSC_nm39cg1532-0.810.81CTACTTTCAAT0001CTCTATGGATTTCCCTATTCAGGACATTTTCTATAAACG (SEQID NO: 1322) MDSC_nm40cg1939-0.730.74TATGCTTACTC9285CCTCTCCCTCTTGTCTGTGTCCCTGTGTGGCCTGAAGCG (SEQID NO: 1323) MDSC_nm41cg2116-0.560.53CGGAGAGCCA4050ACACCACCAGTCAGTCACCCAAGCTGGAAATTTAAGCATC (SEQID NO: 1324) MDSC_nm42cg2120-0.670.71CGTCTGCAAGA4530ACAGGGGAGAACTAAGGTCCCAAGCAGCAAAAGTTAAAA(SEQ ID NO:1325) MDSC_nm43cg072-0.700.68CGGCATCTTCA60017TTTGAGTGGGTGCGGGAAGGACCTCATTTTGGAACCACA (SEQID NO: 1326) MDSC_nm44cg0619-0.830.74CGCGTGCCTCT3597GTGCAGTCAGTGAG AAGGGCTCCCGTTCAGAATGGGCAG (SEQID NO: 1327) MDSC_nm45cg2617-0.650.63CGTGAGCCAG4398AGAGAGCTGGCTTTCAGTGTTGTCACCATGGTTACTGCTA(SEQ ID NO:1328) MDSC_nm46cg2458-0.560.63CGACTGCTCCT7185CTGGCAAGCAGGACCCATTTCTAAAGCATGAGTCACTAC(SEQ ID NO:1329) MDSC_nm47cg0582-0.790.78CGCTTCAGACG7190CATCTCTTCTCAGTGAGTCAGCTGTGGGCCCCACTCAGG (SEQID NO: 1330) MDSC_nm48cg0317-0.720.72CGGAAAACTT6993GCTAATGCTGGCTGATTCTCATTGCTGGGTTTACTAGTTC (SEQID NO: 1331) MDSC_nm49cg0337-0.850.70CGCTTTATGGA2334GCAGCAAAGAAAGTAGTTTCTTGAGATGGGTTCTACTCT (SEQID NO: 1332) MDSC_nm50cg2187-0.760.76TAAAATTATTT7464TTTTCCCTAAACCCAATCTCTCCTCTTCCTCCTCTGTCG (SEQID NO: 1333) MDSC_nm51cg0985-0.740.68CGCTGTCAGGA4726ATTGTCTCCTGGTTCAACCCACTCCTGCCTTAGGCCCAC (SEQID NO: 1334) MDSC_nm52cg1649-0.600.57CGATGGTGAG0209CAAAAGGTGTTGACAGGCCTGGCATGGTGACTCACCCCTG(SEQ ID NO:1335) MDSC_nm53cg181-0.690.64TCCAAGTCACA14313CAGCCCTTAAATGAGCCACCAGGTTACCTTTGCATCACG (SEQID NO: 1336) MDSC_nm54cg223-0.720.74CGGAGGCCCA07974GAGAAGGGAAGTGACATGCTCAAGGTAACACTGCTAACCA(SEQ ID NO:1337) MDSC_nm55cg191-0.750.71CGTGAGGTTGT32462GTCTTACTGAGCTCACATCATAATTCCTGTGTGCACAGA (SEQID NO: 1338) MDSC_nm56cg1222-0.630.63CGAGGACAGT9979TCCTCCAGAAATCCAGGTCAGTCACAAGACAAAGAAAAGA(SEQ ID NO:1339) MDSC_nm57cg0609-0.570.47CGGCCTCTGAG3152AGCTGACACGGAACTTGCATCATTTCTGATGCTTGGCTC (SEQID NO: 1340)
TABLE 4JTotal Lymphocytes MarkerNon-CD4+CD8+Baso-Eosino-Neutro-Clas-clas-ThCD4+Cyto-philphilphilsicalsicalNKCD4+Cent-ThxicNKMarker-Target-Acces-Granulo-Granulo-Granulo-Mono-Mono-clas-B-ThCD4+CD4+ralEffectT-T-DiscoveryIDIDSYMBOLsioncytescytescytescytescytessicalCellsnaiveTh1Th2Mem.Mem.CellsCellsFragmentLYMP_nm1cg14437551LTANM_0005950.940.960.950.950.960.130.040.110.020.020.020.030.040.03AGAGGAAGCGGCAGTGGCAGCGTGGCAGGCAGCGGGCGGGTTCTAGGTCG(SEQ ID NO: 1341) LYMP_nm2cg02668248KLF2NM_0162700.890.900.930.900.800.040.060.100.020.030.020.060.030.05CGTGCCTTCTCGCGCTCCGATCACCTGGCGCTGCACATGAAACGGCACAT(SEQ ID NO: 1342) LYMP_nm3cg00446123LIME1NM_0178060.780.680.890.780.720.030.050.050.030.030.030.030.020.02TCAGAACAGTGCGGGCTAGAGGCGCACACGTTTCATCTAGGCTTCGGGCG(SEQ ID NO: 1343) LYMP_nm4cg21959598VOPP1NM_0307960.840.810.890.870.840.080.120.170.100.110.130.120.170.08ATAAAAGCAACCCAGGGAGCTATTTGGTGGCTTCTGGCTTCTGACTGCCG(SEQ ID NO: 1344) LYMP_nm5cg17161520TBC1D10CNM_1985170.830.820.810.790.730.080.050.090.110.080.100.150.050.09GGTGCTCACTGGCTCCAGACGTGGATCTGCAGCTGGGAATCAAGTGATCG(SEQ ID NO: 1345) LYMP_nm6cg03961551RUNX3NM_0010316800.610.770.850.850.790.080.130.080.060.060.070.080.070.07TTTCCCAGTCAGCAGGATGGGCACTGCAGATGTGTGTCTGCATGCCAGCG(SEQ ID NO: 1346) LYMP_nm7cg04450994SLC22A23NM_0219450.530.780.790.770.810.040.170.030.010.030.030.030.040.02CGGGCTCTCACACGTGGGCCACCATCCGCCTGCCCCAGTCACCCCGGGGC(SEQ ID NO: 1347) LYMP_nm8cg18920397LY9NM_0010336670.810.830.830.680.630.080.140.090.050.050.050.070.050.06CGCAGGCAGGTAGAGGTCCCAAGTCTATTCAGGGCCTCATTTGTGACTGA(SEQ ID NO: 1348) LYMP_nm9cg18825221RAD51L1NM_1335090.640.660.730.710.650.110.040.040.020.030.020.030.040.07AGAAAGCACCACAGGTAATAAAAACACCTAAAAAGGTCAGCAGAAACTCG(SEQ ID NO: 1349) LYMP_nm10cg11327657C21orf0NM_0581900.020.020.010.020.040.940.970.950.970.960.980.960.960.97CGCAACCCCCAGTGACACAACCCCCAGTGACGCAACCCCGTGACCCAATGSEQ ID NO: 1350) LYMP_nm11CG11597902——0.030.020.100.030.060.950.950.940.960.960.950.950.970.96CGAGGAGCGGGCGTGCTGCGCTGCTTCTCTTTGAGTCATCTGGGTCCTCG (SEQID NO: 1351) LYMP_nm12cg21159128SSBP3NM_0010099550.030.010.000.020.050.950.860.950.930.920.940.930.960.93CGACAATGTAAGCCTCGCCCCCTGCCTGTTGCTCTCGTCCCCACGGCCTG(SEQ ID NO: 1352) LYMP_nm13cg05327789SLCO4A1NM_06163540.030.010.010.010.070.820.950.950.940.950.930.950.960.87CGGCCACGGCGGGCACTCAGCATTTCCTGATGACAGAACAGTGCCGTTGG(SEQ ID NO: 1353) LYMP_nm14cg26709988CRISPLD2NM_0314760.190.030.030.040.090.960.960.950.960.960.970.950.970.97CGCAAAAGCCTTGCAACACACAACAGCACAGACAAACCCCGCAGACACGG(SEQ ID NO: 1354) LYMP_nm15cg05260077——0.050.030.030.020.060.900.910.900.910.900.890.890.920.90ATTTCGAAATAAAGGAGCTTGCATGAATGACGATTTCCAAACTTCTCTCG(SEQ ID NO: 1355) LYMP_nm16cg10690440——0.130.240.060.020.060.950.970.960.960.970.980.960.970.95CCTGCGCTCTGACACCAGCCGTGTAAGGGCACAGACTCGGCTGCTGTTCG(SEQ ID NO: 1356) LYMP_nm17cg20429104ZNF516NM_0146430.280.050.020.040.080.960.970.960.960.960.970.960.960.93CGTTCAGATCTGTTGCGACTCTTCAGATCACTTCCCGTTTTGCAATCACG(SEQ ID NO: 1357) LYMP_nm18cg0286247UBR4NM_0207650.070.030.030.040.090.900.860.900.920.910.920.930.930.92CACATCCTGCCCCCTGAGCAGTGGAGAGCCACACGTGTGGAAATCTTGCG(SEQ ID NO: 1358) LYMP_nm19cg00500359OSBPL5NM_0208960.040.020.010.160.260.920.970.960.960.960.970.960.970.96CGCCCACTTTGCCGGTGGGACAGAGTGGCTGACGGCGTGTGGCACAGGCG(SEQ ID NO: 1359) LYMP_nm20cg11186858——0.110.050280.050.100.950.950.960.970.980.970.960.980.97CGCACTAACGTGAATGCCGCATGTACAGATGACCACAGTGCTCGGAGGGT(SEQ ID NO: 1360) LYMP_nm21cg15085899NCOR2NM_0063120.030.060.010.010.010.720.430.890.970.970.980.960.970.97GAGTGGCAGAGGCGAGAACGGATCGCTGGAGGCCCGACGTCTCGTTCACG(SEQ ID NO: 1361) LYMP_nm22cg08400494CARS2NM_0245370.040.020.040.150.110.950.830.930.950.950.940.940.960.94ATATTTAAGGCATCGCCCCTCAGGGAGCCGAGCACTGATTTCCACAGCCG(SEQ ID NO: 1362) LYMP_nm23cg19851816TUBGCP6NM_0204610.020.020.000.010.030.850.620.830.890.920.900.920.920.93CGTGCGTGCTCCATCTCCCGCAGCCGAGCCGCCCATTGCTCATCTTTTGC(SEQ ID NO: 1363) LYMP_nm24cg23568192——0.050.040.020.050.100.890.870.900.890.880.900.900.940.91AGCGGGTAAGTAATGCATTCAAGGTTGCACAACTAGTAAATGCTTCATCG(SEQ ID NO: 1364) LYMP_nm25cg00168694ETS2NM_0052390.060.070.040.040.080.840.930.920.900.910.910.920.930.87CGTGGGATCCCATGCCACCTTCCTGCCAAATGACCATGTGTAAATTGCTT(SEQ ID NO: 1365) LYMP_nm26cg06298740——0.070.100.040.040.090.900.910.910.910.910.910.920.920.92CGAACCAGGAACTCTCTTATTCCATGGACTGTGGTCTGGGTCAGTAGGCT (SEQID NO: 1366) LYMP_nm27cg20078972BRD4NM_0582430.050.040.030.040.060.870.880.880.890.890.890.900.900.87CGGCTTCTTTAATTGTGCAATCTGTGTCAGTGGGGAAGCACAAATAGGAT(SEQ ID NO: 1367) LYMP_nm28cg26942829GFOD1NM_0189880.060.070.050.050.110.900.910.910.900.900.910.900.920.90CGGAGATTGCCCAACCAAAGAGCAGAAGTTCACAGAATATCTCTTCTTGG(SEQ ID NO: 1368) LYMP_nm29cg03408945C16orf68NM_0241090.260.010.010.010.060.820.880.850.940.930.920.930.920.96CGGGCTCCACCACGAAGCGCAGCTTGCCATCTGCGAGCTGCTCCAGCGCG(SEQ ID NO: 1369) LYMP_nm30cg06373940ERCC3NM_0001220.060.050.060.060.140.900.840.900.920.920.940.910.930.92GTATTTGTTACAGCAGTACCCTATTCCCCGTACCAAAAATCTGTGTTACG(SEQ ID NO: 1370) LYMP_nm31cg25576997C14orf34NR_0267960.050.040.040.040.080.910.860.910.850.850.880.860.900.90AATGATGAAATCCAGCCATTCTGACACTGTTCCTTATCTAGGATCTCTCG (SEQID NO: 1371) LYMP_nm32cg11703212TFDP1NR_0265800.070.050.060.090.130.910.890.920.920.910.930.910.920.94GAGTCTGGAGAGAGCAATGTCTCCATGGAGCGGGTGCCTGGCTGTGGTCG(SEQ ID NO: 1372) LYMP_nm33cg06474225HTRA1NM_0027750.030.210.060.020.040.930.930.920.870.880.900.890.890.84CGGCGAATCTCATCAAACTTTGAGAAAAAAAAACAGCTCATCACAGAGAT(SEQ ID NO: 1373) LYMP_nm34cg04739200MYBNM_0053750.100.040.030.050.080.880.880.880.900.890.890.900.890.88CGCCAGCAAGGTGCATGATCGTCCACCAGGGCACCATTCTGGATAATGTT(SEQ ID NO: 1374) LYMP_nm35cg07283015HRH4NM_0216240.080.060.040.070.150.920.930.910.910.890.900.890.920.91CGGATGAGGTCTGCAGTTGCCCCACCTTACTATCTTGAGAGTTCCCAGGG(SEQ ID NO: 1375) LYMP_nm36cg10456459ETNK1NM_0186380.110.150.060.050.110.930.920.910.920.920.930.940.930.91ACGAATTTAAGCTTTATGCCACAATTTCCCAATTCAACATAAAGCTAACG(SEQ ID NO: 1376) LYMP_nm37cg20312012FERIL5NM_0011133820.080.080.060.050.080.860.860.900.900.910.900.910.910.91GTTTTGTTTCCTCATACCTTACATTGTGAAATACAAAATTAGCTAATGCG(SEQ ID NO: 1377) LYMP_nm38cg04478251ABRNM_0219620.440.110.140.070.100.960.950.940.970.960.960.970.970.97CGCGACGCGCTCATCTGCCACCCACACGAAGACAAAACACAATGGTTATG(SEQ ID NO: 1378) LYMP_nm39cg06030535——0.050.050.050.050.060.890.880.880.880.860.870.880.890.87CAGAGGCCAGAGACTTGAATTTACAAGGAGGGTCCTCAACACAGACATCG(SEQ ID NO: 1379) LYMP_nm40cg07714276RREB1NM_0010037000.140.060.060.050.080.870.870.900.910.910.900.910.920.90CCCTGGTATTTCTCACTTTCTTGCCTAACTTAGCAGAAACATGTATCG (SEQID NO: 1380) LYMP_nm41cg17374091TRIM27NM_0065100.260.050.020.020.050.890.900.890.910.890.900.900.910.91GTTACACTATAAATAGATGTTCACTGACCAAATACTCCTACTAGTTCTCG(SEQ ID NO: 1381) LYMP_nm42cg02353916LOC285550NM_0011451910.040.020.070.030.070.890.850.850.890.880.860.900.880.85CGGCATTGATGTTGCTTCACGTTGCTGATGCTTAAGCAATGTATATTGTG(SEQ ID NO: 1382) LYMP_nm43cg23506143——0.120.080.060.040.050.910.890.850.860.880.900.860.920.90CGTCGTCTTTAAAATGTGCTATCATTTCCTTGTTATAGTTGTGCAAGATT (SEQID NO: 1383) LYMP_nm44cg13086983ECE1NM_0011133480.060.070.040.050.090.880.830.880.900.900.900.900.900.89TGGCTCCAGTTTCCAAGTGACGCAACCAAGTGTCTGGATTCAGAGAATCG(SEQ ID NO: 1384) LYMP_nm45cg12249234KSR1NM_0142380.080.050.040.040.080.860.860.880.870.890.870.890.900.86ACAAATGTAAAAGCCTGGCAGCTTCCCCAGGAGAGTGCGGGTATGGGCCG(SEQ ID NO: 1385) LYMP_nm46cg13381110PHLPP1NM_1944490.120.080.060.060.140.830.890.900.930.930.910.920.940.94CATAGTGGCGTGTCGTAATAATCTGGCAGCTGGTCCAGCTGGTAGTGCCG(SEQ ID NO: 1386) LYMP_nm47cg01990910SNX29NM_0010805300.010.030.020.010.030.380.590.880.960.970.960.960.930.94CGCCGGCCAAATGCAACCAGCAGAGATATGACCCCGACCCGTCTAAAGCC(SEQ ID NO: 1387) LYMP_nm48cg25103337H6PDNM_0042850.040.040.020.020.050.760.730.870.890.900.880.890.890.88TGGGGCCAACAGGCATGATTACCACACAGGATGTTAGGCAAGGGGTTCCG(SEQ ID NO: 1388)
In table 4, regions that contain CpGs that are specific for the blood cell types granulocytes, monocytes, CD4+ cells, cytotoxic T-cells, B-cells, Natural Killer-cells, and Natural Killer T-cells are listed, as well as their SEQ ID NOs for the so-called “discovery fragment” (preferred region) and the discriminative “region of interest” (more preferred region). The discovery fragments comprise at least one CpG that is specific for the cell type as indicated, and thus suitable to distinguish this cell type from all other cell types of the haemogram. The discriminative region of interest (ROI) sequences are regions that are positioned around the discovery region, and which form the basis for the design of the specific assay for a specific cell type as indicated, and contain additional relevant CpGs, that is, a sequence of CpGs that can also be used in order to distinguish between the call types as indicated.
In table 4A to 4J, regions that contain CpGs that are specific for the respective blood cell types as shown in each table header are listed. The sequence provided in the column “discovery fragment” is the preferred region and comprises at least one CpG that is specific for the cell type of the respective table (identifiable by the shown data). Also comprised in the context of the various embodiments and aspects of the invention is a region 500 base pairs upstream and downstream of (therefore “around”) the sequence of the “discovery fragment” in the human genome for each marker. The region 500 base pairs upstream and downstream of the “discovery fragment” are the discriminative ROI of the marker of the tables 4A to 4J.
The present invention therefore also pertains to a bisulfite conversion of at least one CpG position within any one of the “discovery fragments” or ROI (500 bp up and downstream for each “discovery fragment” in the human genome) of any one of the Tables 4 and 4A to 4J as shown above, which is indicative for a respective cell type as listed in the tables 4. The T-lymphocytogram in all of the embodiments and aspects of the invention may therefore contain any of the cell types listed in the above tables 4 and 4A to 4J, and any combinations of these cell types.
An additional region for neutrophilic granulocytes (nGRC) is derived from the Lipocalin-2, neutrophil gelatinase-associated lipocalin (LCN2) genomic region (Ensembl-ID: ENSG00000148346); herein designated AMP1730. The AMP 1730 genomic sequence and the discriminative ROI 1132 are SEQ ID NOs: 686 and 685 respectively. See also FIG. 2.
Additional regions for eosinophilic granulocytes (eGRC) are derived from the proteoglycan 2 (PRG2) genomic region (Ensembl-ID: ENSG00000186652), herein designated as AMP 2034 and 2035, respectively. The AMP 2034 and 2035 genomic sequences, and the discriminative ROI1403 are SEQ ID NOs: 687, 688, and 689, respectively. See also FIG. 3.
Preferably, the cell-specific gene regions as described herein are selected to discriminate one cell type or subpopulation of cells from all other cell types, such as the leukocytogram, T-lymphocytogram, granulocytogram, monocytogram, B-lymphocytogram and/or NK cytogram as described herein. Thus, highly specific cell-type markers are used as a basis for identification and quantification that are not based on protein expression levels but on cell type-specific epigenetic information. The method provides a clear yes/no information and is independent of thresholding as the cell-specific CpG-rich genomic region is bisulfite convertible or not, is detectable by qPCR or not as well as genomic copies do not vary. The method also detects and identifies as well as quantifies a potentially unlimited number of subpopulations of cells, and the detection limit for, for example, regulatory T cells is at 0.3%.
Preferred is a method according to the present invention, wherein the cells that are detected and thus for the epigenetic haemogram are selected from a leukocytogram, and/or a T-lymphocytogram, and/or a granulocytogram, and/or a monocytogram, and/or a B-lymphocytogram, and/or a NK cytogram.
Preferably, said marker regions as analyzed are specific for the cells of a pre-selected haemogram, and these cells are preferably selected from T-lymphocytes, natural killer cells, B-lymphocytes, monocytes, granulocytes, and combinations thereof, for a leukocytogram, selected from CD3+CD4, CD4+ memory, CD4+ effector cells, CD4+ naïve, CD3+CD8+, CD8 positive, CD8+ memory, CD8+ effector cells, CD8+ naïve, CD3+CD8−CD4−, CD3+CD8+CD4+, NKT cells, iTreg, Treg, Tfh, Th1, Th2, TH9, Th17, Th19, Th21, Th22, memory and effector T helper cells, and combinations thereof, for a T-lymphocytogram, selected from basophilic, eosinophilic, neutrophilic granulocytes, and/or granulocytic myeloid-derived suppressor cells, and combinations thereof, for a granulocytogram, selected from CD14+ monocytes, CD14− monocytes, macrophages, plasmacytoid dendritic cells, myeloid-dendritic cells, intermediate monocytes, classical monocytes, non-classical monocytes, and/or overall dendritic cells, and combinations thereof, for a monocytogram, selected from naïve B cells, pre B cells, memory B cells, transitional B cells and/or immature B cells, and combinations thereof, for a B cell cytogram, and selected from CD56dim and/or CD56bright NK cells for an NK cytogram.
In contrast to the term “cell-specific regions”, the term “cell-unspecific regions” herein shall mean genetic regions in the genome of cells and/or nucleic acids that are selected to be unspecific, i.e. are specific for more than one, preferably all, cell type and/or subpopulation of cells. These cell-unspecific regions also include the genes of certain markers (such as, for example, certain protein markers), such as 5′ untranslated regions, promoter regions, introns, exons, intron/exon borders, 3′ regions, CpG islands, and in particular include specific regions as amplified after bisulfite treatment (amplicons) that are “informative” for more than one cell type and/or subpopulation of cells. Examples for these cell-unspecific regions are known from the literature, and are selected from, for example regions comprising a housekeeping gene, such as GAPDH, ACTB (beta-actin), UBC (ubiquitin C), ribosomal proteins (e.g. RPS27A, RPS20, RPL11, RPL38, RPL7, RPS11, RPL26L1), CALR (calreticulin), ACTG1 (gamma actin) RPS20 (ribosomal protein S20), HNRPD (ribonucleoprotein D), NACA (nascent polypeptide-associated complex subunit alpha), NONO (octamer-binding protein), PTMAP7 (prothymosin), GFRA4 (GDNF receptor alpha-4), CDC42 (GTP-binding protein), EIF3H (translation initiation factor), UBE2D3 (ubiquitin-conjugating enzyme), and genes as described in, for example, She et al. (Definition, conservation and epigenetics of housekeeping and tissue-enriched genes. BMC Genomics. 2009 Jun. 17; 10:269.), and PCT/EP2011/051601.
The method according to the present invention generally identifies the quantitative cellular composition of a biological sample. Preferred is a method according to the present invention, wherein said biological sample is a sample of unknown cellular composition. Nevertheless, also samples of known cellular composition, or even partially known composition can be quantified.
Biological samples to be analyzed can be stored fresh-frozen, paraffin-embedded or Heparin, Citrate or EDTA-stabilized as cells in samples do not need to be intact. The present method is very robust and allows, in contrast to flow cytometry, a parallel, independent assessment of cell identity and quantity as well as sample composition. A very good correlation to FACS is provided, too.
The biological sample to be analyzed can be any sample comprising one or more type(s) of cells or that is suspected of comprising one or more type(s) of cells that are to be quantified. Preferred materials/biological samples are selected from a blood sample, in particular peripheral, capillary or venous blood samples, blood clots, or samples that are considered to contain blood cells as e.g. synovial fluid, lymph fluid, sputum, urine, tumor samples, as well as other fluid and tissue samples, histological preparations, DBS, artificially generated cells and mixtures thereof (e.g. cell culture samples).
Yet another aspect of the present invention then relates to a method according to the present invention, further comprising the step of concluding on the immune status of a mammal based on said epigenetic haemogram as produced.
Yet another aspect of the present invention then relates to a method according to the present invention, further comprising the step of monitoring said cellular composition in said biological sample as identified by comparing said composition and/or haemogram as identified with the composition in an earlier biological sample taken from the same mammal, and/or with the composition in a control sample. In this aspect, for example, modifications and changes of the cellular composition in a patient can be monitored during a medical treatment.
Yet another aspect of the present invention then relates to a method for diagnosing a disease or a predisposition for a disease, comprising a method according to the present invention as described above, and the step of concluding on the disease or a predisposition for said disease based on the cellular composition in said biological sample as identified. In this aspect, for example, modifications and changes of the cellular composition in a patient can be used for diagnosing a disease or a predisposition for a disease, in particular when the sample is compared to a sample of a healthy subject or to medical reference ranges. Preferably, said biological sample is a blood sample, in particular a whole or peripheral blood sample, and said cell-specific regions in the genome of cells in said sample are selected from regions specific for blood cell types. The disease to be diagnosed can be selected from the group consisting of immune diseases or conditions, transplant rejections, infection diseases, cancer, neurological diseases, allergy, primary and secondary immune deficiencies and hematologic malignancies such as, for example, lymphatic neoplasms, mature B-cell neoplasms, mature T- and NK-cell neoplasms, Hodgkin lymphomas, lympho-proliferative processes after transplantations, HIV and AIDS, Graft versus Host disease, rheumatoid arthritis, lupus erythematosus, breast cancer, colorectal cancer, esophageal cancer, stomach cancer, leukemia/lymphoma, lung cancer, prostate cancer, uterine cancer, skin cancer, endocrine cancer, kidney cancer, urinary cancer, pancreatic cancer, other gastrointestinal cancers, ovarian cancer, cervical cancer, head and neck cancer, adenomas, birth defects, myopathies, mental retardation, obesity, diabetes, gestational diabetes, multiple sclerosis, and asthma.
In one preferred embodiment of the present invention, the diagnostic use of the epigenetic haemogram is also based on the use of ratios of different populations and/or/to different subpopulations (subhaemograms) and/or/to of cells belonging to one subhaemogram according to the said epigenetic haemogram. Such ratios are e.g. but are not limited to, population of regulatory T cells in relation to CD3+ T-lymphocytes, or regulatory T cells in relation to population of CD4+ T-lymphocytes, or regulatory T cells in relation to population of CD8+ T-lymphocytes, or CD3+ T-lymphocytes to CD4+ T-helper cells, or CD3+ T-lymphocytes to CD8+ cytotoxic T cells, or CD4+ T-helper cells to CD8+ cytotoxic T-cells, or Th1 to Th2, or Th1 to Th17, or Th2 to Th17, or memory or naïve CD4+ T-helper cells to CD3+ T-lymphocytes, or memory CD8+ cytotoxic T-cells to CD3+ T-lymphocytes, all as subpopulations of the T-lymphocytogram; or CD3+ T-lymphocytes related to neutrophilic granulocytes, or macrophages to CD4+ T-helper cells; CD4+ T-lymphocytes related to neutrophilic granulocytes, or CD8+ T-lymphocytes related to neutrophilic granulocytes all as relations between cells of different subhaemograms; or CD3− T-lymphocytes related to granulocytes, or B-lymphocytes to CD3+ T-lymphocytes, or monocytes to CD3 T-lymphocytes, or monocytes to B-lymphocytes all as ratios out of populations of the leukocytogram; or CD3+ T-lymphocytes or monocytes or B-lymphocytes, or granulocytes or NK cells related to overall leukocytes.
But also other ratios of subpopulations assessed according to the present invention and according to the epigenetic haemogram can be used as a diagnostic method. The disease can be selected from the group consisting of immune diseases or conditions, transplant rejections, infection diseases, cancer, neurological diseases, allergy, primary and secondary immune deficiencies and hematologic malignancies such as, for example, lymphatic neoplasms, mature B-cell neoplasms, mature T- and NK-cell neoplasms, Hodgkin lymphomas, lympho-proliferative processes after transplantations, HIV and AIDS, Graft versus Host disease, rheumatoid arthritis, lupus erythematosus, breast cancer, colorectal cancer, esophageal cancer, stomach cancer, leukemia/lymphoma, lung cancer, prostate cancer, uterine cancer, skin cancer, endocrine cancer, kidney cancer, urinary cancer, pancreatic cancer, other gastrointestinal cancers, ovarian cancer, cervical cancer, head and neck cancer, adenomas, birth defects, myopathies, mental retardation, obesity, diabetes, gestational diabetes, multiple sclerosis, and asthma. The diagnostic use encompasses but is not limited to the diagnosis of a disease and/or the follow-up of a disease and/or the predisposition for a disease and/or the monitoring of an effect of a chemical or biological substance.
The epigenetic haemogram of the invention is in another embodiment used for the assessment of the risk to develop a disease in a patient, therefore for diagnostic purposes. In one preferred embodiment of the present invention, the use of the epigenetic haemogram for the assessment of the risk to develop a disease is also based on the use of ratios of different populations and/or/to different subpopulations (subhaemograms) and/or/to of cells belonging to one subhaemogram according to the said epigenetic haemogram. Such ratios are e.g. but are not limited to, population of regulatory T cells in relation to CD3+ T-lymphocytes, or regulatory T cells in relation to population of CD4+ T-lymphocytes, or regulatory T cells in relation to population of CD8+ T-lymphocytes, or CD3+ T-lymphocytes to CD4+ T-helper cells, or CD3+ T-lymphocytes to CD8+ cytotoxic T cells, or CD4+ T-helper cells to CD8+ cytotoxic T-cells, or Th1 to Th2, or Th1 to Th17, or Th2 to Th17, or memory or naïve CD4+ T-helper cells to CD3+ T-lymphocytes, or memory CD8+ cytotoxic T-cells to CD3+ T-lymphocytes, all as subpopulations of the T-lymphocytogram; or CD3+ T-lymphocytes related to neutrophilic granulocytes, or macrophages to CD4+ T-helper cells; CD4+ T-lymphocytes related to neutrophilic granulocytes, or CD8+ T-lymphocytes related to neutrophilic granulocytes all as relations between cells of different subhaemograms; or CD3+ T-lymphocytes related to granulocytes, or B-lymphocytes to CD3+ T-lymphocytes, or monocytes to CD3+ T-lymphocytes, or monocytes to B-lymphocytes all as ratios out of populations of the leukocytogram; or CD3+ T-lymphocytes or monocytes or B-lymphocytes, or granulocytes or NK cells related to overall leukocytes.
But also other ratios of subpopulations as assessed in accordance with the present invention and according to the epigenetic haemogram can be used to assess the risk for developing a disease. The disease for the herein described embodiment can be selected from the group consisting of immune diseases or conditions, transplant rejections, infection diseases, cancer, neurological diseases, allergy, primary and secondary immune deficiencies and hematologic malignancies such as, for example, lymphatic neoplasms, mature B-cell neoplasms, mature T- and NK-cell neoplasms, Hodgkin lymphomas, lympho-proliferative processes after transplantations, HIV and AIDS, Graft versus Host disease, rheumatoid arthritis, lupus erythematosus, breast cancer, colorectal cancer, esophageal cancer, stomach cancer, leukemia/lymphoma, lung cancer, prostate cancer, uterine cancer, skin cancer, endocrine cancer, kidney cancer, urinary cancer, pancreatic cancer, other gastrointestinal cancers, ovarian cancer, cervical cancer, head and neck cancer, adenomas, birth defects, myopathies, mental retardation, obesity, diabetes, gestational diabetes, multiple sclerosis, and asthma. The diagnostic use encompasses but is not limited to the diagnosis of a disease and/or the follow-up of a disease and/or the predisposition and/or the assessment of a risk for a disease and/or the monitoring of an effect of a chemical or biological substance.
As indicated, the above mentioned ratios as assessed in accordance with the present invention bear the potential to indicate e.g. the risk to develop a certain disease during the life time of a subject. A clinical role in risk assessment was found for the ratio of regulatory T-lymphocytes to CD3+ T-lymphocytes. Particularly preferred in the context of the present invention is that an increase in the ratio of regulatory T-lymphocytes to CD3+T-lymphocytes indicates a risk to develop cancer (cancerous disease) during life time. The cancer is selected from but not limited to the list as provided herein above, wherein a high impact of an increased ratio of regulatory T-lymphocytes to CD3+ T-lymphocytes is expected for the development of lung cancer, which is particularly preferred. Furthermore, ratios bear the potential to predict the development of Graft versus Host Disease wherein an increased ratio of regulatory T-lymphocytes to CD4+ T-lymphocytes within the first two weeks after stem cell transplantation predicts the development of a graft versus host disease.
Yet another aspect of the present invention then relates to a method for identifying the effect of a chemical or biological substance or drug on the composition of cells, comprising performing the method according to the present invention as described above, preferably on a blood sample obtained from a mammal treated with or exposed to said substance, and comparing the composition of cells in said sample with the composition of samples before treatment or with the composition of an untreated sample. The mammal to be treated with said chemical or biological substance or drug might be healthy or suffers from a disease selected from the group consisting of immune diseases or conditions, transplant rejections, infection diseases, cancer, neurological diseases, allergy, primary and secondary immune deficiencies and hematologic malignancies such as, for example, lymphatic neoplasms, mature B-cell neoplasms, mature T- and NK-cell neoplasms, Hodgkin lymphomas, lymphoproliferative processes after transplantations, HIV and AIDS, Graft versus Host disease, rheumatoid arthritis, lupus erythematosus, breast cancer, colorectal cancer, esophageal cancer, stomach cancer, leukemia/lymphoma, lung cancer, prostate cancer, uterine cancer, skin cancer, endocrine cancer, kid-kidney cancer, urinary cancer, pancreatic cancer, other gastrointestinal cancers, ovarian cancer, cervical cancer, head and neck cancer, adenomas, birth defects, myopathies, mental retardation, obesity, diabetes, gestational diabetes, multiple sclerosis, and asthma.
Yet another aspect of the present invention then relates to a diagnostic kit and its use, comprising materials for performing the method according to the invention as described herein, optionally with instructions for use. The diagnostic kit particularly contains oligonucleotides (e.g. for producing amplicons) specific for regions of interest, bisulfite reagents, and/or components for PCR. The diagnostic kit and its use encompasses but is not limited to the diagnosis of a disease and/or the follow-up of a disease and/or the predisposition and/or the assessment of a risk for a disease and/or the monitoring of an effect of a chemical or biological substance.
As mentioned above, currently, in both, clinical diagnostics and research, and drug development, a new method to provide a precise and comprehensive quantification of leukocytes and their subpopulations is desired even if biological samples are not intact anymore. The present invention, overcomes most problems of current, routinely used quantitative methods, flow cytometry and immune histochemistry, but more importantly, overcomes several biochemical and technical problems of qPCR in regard to absolute quantification of target cells. The present invention thus provides a method to effectively detect and quantify the different cell populations. In particular, the present method for the first time allows for an expression-independent method for the assessment of a comprehensive blood cell picture. Moreover, the present invention enables flexible time framing which is not dependent on quick sample processing but rather allows long term sample storage and individual coordination between sample collecting and sample processing.
SEQ ID No. 1 to 689 show sequences as used in the context of the present invention.